{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Загрузка набора данных"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Rating</th>\n",
       "      <th>Spec_score</th>\n",
       "      <th>No_of_sim</th>\n",
       "      <th>Ram</th>\n",
       "      <th>Battery</th>\n",
       "      <th>Display</th>\n",
       "      <th>Camera</th>\n",
       "      <th>External_Memory</th>\n",
       "      <th>Android_version</th>\n",
       "      <th>Price</th>\n",
       "      <th>company</th>\n",
       "      <th>Inbuilt_memory</th>\n",
       "      <th>fast_charging</th>\n",
       "      <th>Screen_resolution</th>\n",
       "      <th>Processor</th>\n",
       "      <th>Processor_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Samsung Galaxy F14 5G</td>\n",
       "      <td>4.65</td>\n",
       "      <td>68</td>\n",
       "      <td>Dual Sim, 3G, 4G, 5G, VoLTE,</td>\n",
       "      <td>4</td>\n",
       "      <td>6000</td>\n",
       "      <td>6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>13</td>\n",
       "      <td>9999.0</td>\n",
       "      <td>Samsung</td>\n",
       "      <td>128 GB inbuilt</td>\n",
       "      <td>25W Fast Charging</td>\n",
       "      <td>2408 x 1080 px Display with Water Drop Notch</td>\n",
       "      <td>Octa Core Processor</td>\n",
       "      <td>Exynos 1330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Samsung Galaxy A11</td>\n",
       "      <td>4.20</td>\n",
       "      <td>63</td>\n",
       "      <td>Dual Sim, 3G, 4G, VoLTE,</td>\n",
       "      <td>2</td>\n",
       "      <td>4000</td>\n",
       "      <td>6</td>\n",
       "      <td>13.0</td>\n",
       "      <td>Memory Card Supported, upto 512 GB</td>\n",
       "      <td>10</td>\n",
       "      <td>9990.0</td>\n",
       "      <td>Samsung</td>\n",
       "      <td>32 GB inbuilt</td>\n",
       "      <td>15W Fast Charging</td>\n",
       "      <td>720 x 1560 px Display with Punch Hole</td>\n",
       "      <td>1.8 GHz Processor</td>\n",
       "      <td>Octa Core</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Samsung Galaxy A13</td>\n",
       "      <td>4.30</td>\n",
       "      <td>75</td>\n",
       "      <td>Dual Sim, 3G, 4G, VoLTE,</td>\n",
       "      <td>4</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>12</td>\n",
       "      <td>11999.0</td>\n",
       "      <td>Samsung</td>\n",
       "      <td>64 GB inbuilt</td>\n",
       "      <td>25W Fast Charging</td>\n",
       "      <td>1080 x 2408 px Display with Water Drop Notch</td>\n",
       "      <td>2 GHz Processor</td>\n",
       "      <td>Octa Core</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Samsung Galaxy F23</td>\n",
       "      <td>4.10</td>\n",
       "      <td>73</td>\n",
       "      <td>Dual Sim, 3G, 4G, VoLTE,</td>\n",
       "      <td>4</td>\n",
       "      <td>6000</td>\n",
       "      <td>6</td>\n",
       "      <td>48.0</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>12</td>\n",
       "      <td>11999.0</td>\n",
       "      <td>Samsung</td>\n",
       "      <td>64 GB inbuilt</td>\n",
       "      <td>NaN</td>\n",
       "      <td>720 x 1600 px</td>\n",
       "      <td>Octa Core</td>\n",
       "      <td>Helio G88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Samsung Galaxy A03s (4GB RAM + 64GB)</td>\n",
       "      <td>4.10</td>\n",
       "      <td>69</td>\n",
       "      <td>Dual Sim, 3G, 4G, VoLTE,</td>\n",
       "      <td>4</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>13.0</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>11</td>\n",
       "      <td>11999.0</td>\n",
       "      <td>Samsung</td>\n",
       "      <td>64 GB inbuilt</td>\n",
       "      <td>15W Fast Charging</td>\n",
       "      <td>720 x 1600 px Display with Water Drop Notch</td>\n",
       "      <td>Octa Core</td>\n",
       "      <td>Helio P35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1365</th>\n",
       "      <td>TCL 40R</td>\n",
       "      <td>4.05</td>\n",
       "      <td>75</td>\n",
       "      <td>Dual Sim, 3G, 4G, 5G, VoLTE,</td>\n",
       "      <td>4</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Memory Card (Hybrid)</td>\n",
       "      <td>12</td>\n",
       "      <td>18999.0</td>\n",
       "      <td>TCL</td>\n",
       "      <td>64 GB inbuilt</td>\n",
       "      <td>15W Fast Charging</td>\n",
       "      <td>720 x 1612 px</td>\n",
       "      <td>Octa Core</td>\n",
       "      <td>Dimensity 700 5G</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1366</th>\n",
       "      <td>TCL 50 XL NxtPaper 5G</td>\n",
       "      <td>4.10</td>\n",
       "      <td>80</td>\n",
       "      <td>Dual Sim, 3G, 4G, VoLTE,</td>\n",
       "      <td>8</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Memory Card (Hybrid)</td>\n",
       "      <td>14</td>\n",
       "      <td>24990.0</td>\n",
       "      <td>TCL</td>\n",
       "      <td>128 GB inbuilt</td>\n",
       "      <td>33W Fast Charging</td>\n",
       "      <td>1200 x 2400 px</td>\n",
       "      <td>Octa Core</td>\n",
       "      <td>Dimensity 7050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1367</th>\n",
       "      <td>TCL 50 XE NxtPaper 5G</td>\n",
       "      <td>4.00</td>\n",
       "      <td>80</td>\n",
       "      <td>Dual Sim, 3G, 4G, 5G, VoLTE,</td>\n",
       "      <td>6</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>13</td>\n",
       "      <td>23990.0</td>\n",
       "      <td>TCL</td>\n",
       "      <td>256 GB inbuilt</td>\n",
       "      <td>18W Fast Charging</td>\n",
       "      <td>720 x 1612 px</td>\n",
       "      <td>Octa Core</td>\n",
       "      <td>Dimensity 6080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1368</th>\n",
       "      <td>TCL 40 NxtPaper 5G</td>\n",
       "      <td>4.50</td>\n",
       "      <td>79</td>\n",
       "      <td>Dual Sim, 3G, 4G, 5G, VoLTE,</td>\n",
       "      <td>6</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>13</td>\n",
       "      <td>22499.0</td>\n",
       "      <td>TCL</td>\n",
       "      <td>256 GB inbuilt</td>\n",
       "      <td>15W Fast Charging</td>\n",
       "      <td>720 x 1612 px</td>\n",
       "      <td>Octa Core</td>\n",
       "      <td>Dimensity 6020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1369</th>\n",
       "      <td>TCL Trifold</td>\n",
       "      <td>4.65</td>\n",
       "      <td>93</td>\n",
       "      <td>Dual Sim, 3G, 4G, 5G, VoLTE, Vo5G,</td>\n",
       "      <td>12</td>\n",
       "      <td>4600</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50 MP + 48 MP + 8 MP Triple Rear &amp;amp; 32 MP F...</td>\n",
       "      <td>13</td>\n",
       "      <td>119990.0</td>\n",
       "      <td>TCL</td>\n",
       "      <td>256 GB inbuilt</td>\n",
       "      <td>67W Fast Charging</td>\n",
       "      <td>1916 x 2160 px</td>\n",
       "      <td>Octa Core</td>\n",
       "      <td>Snapdragon 8 Gen2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1370 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      Name  Rating  Spec_score  \\\n",
       "0                    Samsung Galaxy F14 5G    4.65          68   \n",
       "1                       Samsung Galaxy A11    4.20          63   \n",
       "2                       Samsung Galaxy A13    4.30          75   \n",
       "3                       Samsung Galaxy F23    4.10          73   \n",
       "4     Samsung Galaxy A03s (4GB RAM + 64GB)    4.10          69   \n",
       "...                                    ...     ...         ...   \n",
       "1365                               TCL 40R    4.05          75   \n",
       "1366                 TCL 50 XL NxtPaper 5G    4.10          80   \n",
       "1367                 TCL 50 XE NxtPaper 5G    4.00          80   \n",
       "1368                    TCL 40 NxtPaper 5G    4.50          79   \n",
       "1369                           TCL Trifold    4.65          93   \n",
       "\n",
       "                                No_of_sim  Ram  Battery  Display  Camera  \\\n",
       "0           Dual Sim, 3G, 4G, 5G, VoLTE,     4     6000        6    50.0   \n",
       "1               Dual Sim, 3G, 4G, VoLTE,     2     4000        6    13.0   \n",
       "2               Dual Sim, 3G, 4G, VoLTE,     4     5000        6    50.0   \n",
       "3               Dual Sim, 3G, 4G, VoLTE,     4     6000        6    48.0   \n",
       "4               Dual Sim, 3G, 4G, VoLTE,     4     5000        6    13.0   \n",
       "...                                   ...  ...      ...      ...     ...   \n",
       "1365        Dual Sim, 3G, 4G, 5G, VoLTE,     4     5000        6    50.0   \n",
       "1366            Dual Sim, 3G, 4G, VoLTE,     8     5000        6    50.0   \n",
       "1367        Dual Sim, 3G, 4G, 5G, VoLTE,     6     5000        6    50.0   \n",
       "1368        Dual Sim, 3G, 4G, 5G, VoLTE,     6     5000        6    50.0   \n",
       "1369  Dual Sim, 3G, 4G, 5G, VoLTE, Vo5G,    12     4600       10     NaN   \n",
       "\n",
       "                                        External_Memory Android_version  \\\n",
       "0                      Memory Card Supported, upto 1 TB              13   \n",
       "1                    Memory Card Supported, upto 512 GB              10   \n",
       "2                      Memory Card Supported, upto 1 TB              12   \n",
       "3                      Memory Card Supported, upto 1 TB              12   \n",
       "4                      Memory Card Supported, upto 1 TB              11   \n",
       "...                                                 ...             ...   \n",
       "1365                               Memory Card (Hybrid)              12   \n",
       "1366                               Memory Card (Hybrid)              14   \n",
       "1367                   Memory Card Supported, upto 1 TB              13   \n",
       "1368                   Memory Card Supported, upto 1 TB              13   \n",
       "1369  50 MP + 48 MP + 8 MP Triple Rear &amp; 32 MP F...              13   \n",
       "\n",
       "         Price  company   Inbuilt_memory       fast_charging  \\\n",
       "0       9999.0  Samsung   128 GB inbuilt   25W Fast Charging   \n",
       "1       9990.0  Samsung    32 GB inbuilt   15W Fast Charging   \n",
       "2      11999.0  Samsung    64 GB inbuilt   25W Fast Charging   \n",
       "3      11999.0  Samsung    64 GB inbuilt                 NaN   \n",
       "4      11999.0  Samsung    64 GB inbuilt   15W Fast Charging   \n",
       "...        ...      ...              ...                 ...   \n",
       "1365   18999.0      TCL    64 GB inbuilt   15W Fast Charging   \n",
       "1366   24990.0      TCL   128 GB inbuilt   33W Fast Charging   \n",
       "1367   23990.0      TCL   256 GB inbuilt   18W Fast Charging   \n",
       "1368   22499.0      TCL   256 GB inbuilt   15W Fast Charging   \n",
       "1369  119990.0      TCL   256 GB inbuilt   67W Fast Charging   \n",
       "\n",
       "                                  Screen_resolution             Processor  \\\n",
       "0      2408 x 1080 px Display with Water Drop Notch   Octa Core Processor   \n",
       "1             720 x 1560 px Display with Punch Hole     1.8 GHz Processor   \n",
       "2      1080 x 2408 px Display with Water Drop Notch       2 GHz Processor   \n",
       "3                                     720 x 1600 px             Octa Core   \n",
       "4       720 x 1600 px Display with Water Drop Notch             Octa Core   \n",
       "...                                             ...                   ...   \n",
       "1365                                  720 x 1612 px             Octa Core   \n",
       "1366                                 1200 x 2400 px             Octa Core   \n",
       "1367                                  720 x 1612 px             Octa Core   \n",
       "1368                                  720 x 1612 px             Octa Core   \n",
       "1369                                 1916 x 2160 px             Octa Core   \n",
       "\n",
       "         Processor_name  \n",
       "0           Exynos 1330  \n",
       "1             Octa Core  \n",
       "2             Octa Core  \n",
       "3             Helio G88  \n",
       "4             Helio P35  \n",
       "...                 ...  \n",
       "1365   Dimensity 700 5G  \n",
       "1366     Dimensity 7050  \n",
       "1367     Dimensity 6080  \n",
       "1368     Dimensity 6020  \n",
       "1369  Snapdragon 8 Gen2  \n",
       "\n",
       "[1370 rows x 17 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import featuretools as ft\n",
    "import re\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from imblearn.over_sampling import RandomOverSampler\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "df = pd.read_csv(\"../data/mobile phone price prediction.csv\")\n",
    "\n",
    "df.drop([\"Unnamed: 0\"], axis=1, inplace=True)\n",
    "df[\"Price\"] = df[\"Price\"].str.replace(\",\", \"\").astype(float)\n",
    "\n",
    "numerical_features = [\n",
    "    \"Ram\",\n",
    "    \"Battery\",\n",
    "    \"Display\",\n",
    "    \"Camera\",\n",
    "]\n",
    "\n",
    "for feature in numerical_features:\n",
    "    df[feature] = df[feature].apply(\n",
    "        lambda x: int(re.search(r\"\\d+\", x).group()) if re.search(r\"\\d+\", x) else None  # type: ignore\n",
    "    )\n",
    "\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Бизнес-цели\n",
    "1. Классифицировать мобильные устройства по ценовым категориям (например, бюджетные, средний класс, флагманы).\n",
    "2. Определить, какие характеристики мобильных устройств наиболее сильно влияют на их рейтинг."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Проверка на пропущенные значения"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Пропущенные данные по каждому столбцу:\n",
      "Name                   0\n",
      "Rating                 0\n",
      "Spec_score             0\n",
      "No_of_sim              0\n",
      "Ram                    0\n",
      "Battery                0\n",
      "Display                0\n",
      "Camera                79\n",
      "External_Memory        0\n",
      "Android_version      443\n",
      "Price                  0\n",
      "company                0\n",
      "Inbuilt_memory        19\n",
      "fast_charging         89\n",
      "Screen_resolution      2\n",
      "Processor             28\n",
      "Processor_name         0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(\"Пропущенные данные по каждому столбцу:\")\n",
    "print(df.isnull().sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Name                 0\n",
      "Rating               0\n",
      "Spec_score           0\n",
      "No_of_sim            0\n",
      "Ram                  0\n",
      "Battery              0\n",
      "Display              0\n",
      "Camera               0\n",
      "External_Memory      0\n",
      "Android_version      0\n",
      "Price                0\n",
      "company              0\n",
      "Inbuilt_memory       0\n",
      "fast_charging        0\n",
      "Screen_resolution    0\n",
      "Processor            0\n",
      "Processor_name       0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "df.dropna(inplace=True)\n",
    "print(df.isnull().sum())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Проверка на выбросы"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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55x5ht9vF7t274+7/0Y9+JAwGg9i/f/8R+z1mzJhe4xL1wQcfxJ2X1DRNjBkzJrZiGRV9/R88eDB225HOkJ1xxhli+vTpcb+fNE0TJ598ctwKXPS1dsopp8St+Pcl+vvirrvuEgcPHhSNjY3iH//4h5g9e3avedzfcYu2WVRUFLcqfOuttwoA4vjjj48793fppZcKRVFij62/c7+/c1SIvlfIJk+eHLdy+stf/lIAEFu3bhVCdJ09KygoELNnz47r8+rVq2Pnv47khhtuEADEv//97z6v2bJliwAgbrrpprjxO9oKmRADO0PWc4UsFX+v2traEq6w9kVRFLFs2bJ+XUvUH8yySDSEzjrrLGzevBnnnnsuPv74Y/ziF79AdXU1ysrK8Je//CV23auvvgpN03D77bdDluNfpt33rFut1th/ezweHDp0CPPmzYPP58POnTuT7udHH32EPXv24LLLLkNLSwsOHTqEQ4cOwev14owzzsDf//73Xtnjvve97w3oZ1x55ZUoKirC6NGjsWjRIni9Xjz99NP48pe/nPD6hoYGfPTRR1iyZAny8/Njtx933HE466yz8Le//W3gDxTABx98gObmZnz/+9+PO5ewaNEiTJo0Ca+//npS7fb3uY6aM2dO7JNXABg7diy+/vWvY+3atYhEIhBC4E9/+hPOOeccCCFiz8mhQ4dQXV0Nt9uNLVu2AAD+9Kc/obCwENddd12vn9PfMw/RFbC1a9fC5/MlvKY/8/Stt96Cqqq44YYb4q655pprkJOT02t8zWYzli5dGnfbSy+9hMmTJ2PSpElxj/v0008HALz99tt9Pg5JknDhhRfib3/7Gzo7O2O3v/DCCygrK8Mpp5wC4IszUH/961+Tyha3c+dOFBUVoaioCJMnT8YjjzyCRYsWxa2WAMD8+fMxZcqUI7alaRpeffVVnHPOOQlfD9GxfemllzBv3jzk5eXFjcuZZ56JSCSCv//970f8OS0tLXErR909++yzKCkpwWmnnRb7mRdffDGef/55RCKRI7bbl9bWVmzYsAEXXXRR7PfVoUOH0NLSgurqauzZswcHDhyI+zfXXHPNUVeHurvjjjtQVFSE0tJSzJs3Dzt27MD9998fO68KDHzcLrzwwtjrAUAs4+S3vvUtGI3GuNtVVY09hv7O/f7O0SNZunRp3Pmy6I6HaObaDz74AC0tLbjmmmvi+nz55Zf3OQe683g8AACn09nnNdH7Ojo6jtpeKqXi75XVaoWiKHjnnXfQ1tZ21J8ZnTtEqcIti0RDbPbs2Xj55Zehqio+/vhjvPLKK3jwwQdxwQUX4KOPPsKUKVOwd+9eyLJ81Ddu27dvx2233YYNGzb0+iPodruT7uOePXsAAIsXL+7zGrfbHfeHfPz48QP6GbfffjvmzZsHg8GAwsJCTJ48Oe6NQk+fffYZAODYY4/tdd/kyZOxdu3aAR3O7k+7kyZNwj//+c8Btdddf57rqIkTJ/b698cccwx8Ph8OHjwIWZbR3t6OX//61/j1r3+d8OdFEyzs3bsXxx577BHH82jGjx+Pm266CQ888ACeffZZzJs3D+eeey6+9a1vxd6c9mee9jW+iqJgwoQJsfujysrKeiUu2LNnD3bs2NHnFqajJUm5+OKL8dBDD+Evf/kLLrvsMnR2duJvf/sbvvvd78aCm/nz5+P888/HXXfdhQcffBCnnnoqvvGNb+Cyyy6D2Ww+YvtAV62kJ598EpIkwWKxYOLEiSguLu51XX9eJwcPHkRHR8dRt7ru2bMH//nPf5IeFwAJtxdHIhE8//zzOO2007Bv377Y7SeeeCLuv/9+rF+/PrYddSBqamoghMBPfvIT/OQnP+mzz2VlZbHvB/p75Tvf+Q4uvPBCBAIBbNiwAQ8//HCvAHKg4zZ27Ni476Pzv7y8POHt0Tf0A5n7/ZmjR9Kzj9HfzT37UlVVFXed0Wjsc9tsd9FgKxqYJdKfoE0Pqfh7ZTab8fOf/xw333wzSkpKcNJJJ+Hss8/GFVdcgdLS0l7tCSGY0INSigEZUZooioLZs2dj9uzZOOaYY7B06VK89NJLvbKY9aW9vR3z589HTk4O7r77blRWVsJisWDLli245ZZbBlX/KPpv77vvPsyYMSPhNQ6HI+777qt1/TF9+nSceeaZSfUv2wz2uQa+eE6+9a1v9fnGI3pOJ1Xuv/9+LFmyBH/+85+xbt06XH/99VixYgXee++9o545SVaieaRpGqZPn44HHngg4b/p+ca4p5NOOgkVFRV48cUXcdlll+G1116D3+/HxRdfHLtGkiT88Y9/xHvvvYfXXnsNa9euxZVXXon7778f7733Xq/53pPdbu/XfB7o6+RINE3DWWed1Weh2mOOOeaI/76goCDhasCGDRvQ0NCA559/Hs8//3yv+5999tmkArLoHP7hD3+I6urqhNf0DBgGOl4TJ06MPQ9nn302DAYDfvSjH+G0006LrTYOdNz6WqHr6/ZEQe7R9GeOHkkq+5LI5MmTAQD/+c9/+vyb8J///AcAYh/Q9BWwJLvC2pdU/b264YYbcM455+DVV1/F2rVr8ZOf/AQrVqzAhg0bep0Va29vj511I0oFBmREGSD6RqGhoQEAUFlZCU3T8Mknn/T5B+add95BS0sLXn75ZXzlK1+J3d79E+2ovv4w9nV7NOlDTk5OxgRN48aNAwDs2rWr1307d+5EYWFhbHVsIJ9cdm83ugUuateuXbH7U6Xncx0V/ZS3u927d8Nms8U+yXc6nYhEIkd9TiorK/Gvf/0LoVCoz4QN/TV9+nRMnz4dt912GzZt2oS5c+di5cqV+J//+Z9+zdPu4zthwoTY7aqqYt++ff2aX5WVlfj4449xxhlnJP2p9EUXXYRf/vKX6OjowAsvvICKigqcdNJJva476aSTcNJJJ+GnP/0pnnvuOVx++eV4/vnnB5SkYLCKioqQk5ODbdu2HfG6yspKdHZ2Jv0anTRpUsLfF88++yyKi4vx2GOP9brv5ZdfxiuvvIKVK1f2GSz19RxFn3+TyTRkv1d+/OMf48knn8Rtt92GN954A8Dgx62/Bjr3+ztHB9OXmpqa2DZUAAiHw6itrT3qhzkLFy6EwWDAM88802dij9/97ncwGo346le/CuCLVbqexZ57rooDA/ud3VMq/15VVlbi5ptvxs0334w9e/ZgxowZuP/++/H73/8+ds2BAwegqmosSCVKBZ4hIxpCb7/9dsJPLKPnn6JbW77xjW9AlmXcfffdvVa6ov8++olo9/ZUVU1Ya8dutyfcwhgNYHr+wZw1axYqKyvxv//7v3FnGqIOHjzY52PUy6hRozBjxgw8/fTTcf3dtm0b1q1bh6997Wux2/p6XIl8+ctfRnFxMVauXIlgMBi7fc2aNdixYwcWLVqUVH/7+1xHbd68OXYGDADq6urw5z//GQsWLIDBYIDBYMD555+PP/3pTwnfqHd/Ts4//3wcOnQIjz76aK/r+vuJeUdHB8LhcNxt06dPhyzLsXHqzzw988wzoSgKHn744bif/dvf/hZut7tf43vRRRfhwIEDePLJJ3vd5/f7+5V97+KLL0YwGMTTTz+NN954AxdddFHc/W1tbb3GJhpkdp8XQ0GWZXzjG9/Aa6+9hg8++KDX/dF+XnTRRdi8eTPWrl3b65r29vZez19Pc+bMwbZt2+Ien9/vx8svv4yzzz4bF1xwQa+v5cuXw+PxJDwHGRWtG9fz9VdcXIxTTz0Vv/rVr3p9IAHo83slNzcX3/3ud7F27Vp89NFHAAY/bv010Ll/tDk6GF/+8pdRUFCAJ598Mu7xPfvss/06M1VeXo6lS5firbfeSlhnbOXKldiwYQOuuuqq2Op5Tk4OCgsLe53J6+tvFNC/39k9peLvlc/nQyAQiLutsrISTqez1+v/ww8/BPBFRmKiVOAKGdEQuu666+Dz+fDNb34TkyZNgqqq2LRpU+zT0Ggyg6qqKvz4xz/GPffcg3nz5uG8886D2WzG+++/j9GjR2PFihU4+eSTkZeXh8WLF+P666+HJEl45plnEr7hnjVrFl544QXcdNNNmD17NhwOB8455xxUVlYiNzcXK1euhNPphN1ux4knnojx48fjN7/5DRYuXIipU6di6dKlKCsrw4EDB/D2228jJycHr7322lAPH+677z4sXLgQc+bMwVVXXRVLe+9yuXDnnXfGPV6g69PxSy65BCaTCeecc07C82Umkwk///nPsXTpUsyfPx+XXnppLO19RUUFbrzxxqT62t/nOmratGmorq6OS3sPdKWVj7r33nvx9ttv48QTT8Q111yDKVOmoLW1FVu2bMFbb72F1tZWAF3pp3/3u9/hpptuwv/93/9h3rx58Hq9eOutt/D9738fX//614/a/w0bNmD58uW48MILccwxxyAcDuOZZ56JBYZA/+ZpUVERbr31Vtx111346le/inPPPRe7du3C448/jtmzZ8cV8e3Lt7/9bbz44ov43ve+h7fffhtz585FJBLBzp078eKLL2Lt2rV9JoOJmjlzZqy/wWCw11awp59+Go8//ji++c1vorKyEh6PB08++SRycnLigv2h8rOf/Qzr1q3D/PnzY6n+Gxoa8NJLL+Gf//wncnNz8V//9V/4y1/+grPPPhtLlizBrFmz4PV6sXXrVvzxj39EbW3tEbdVff3rX8c999yDd999N7YF8S9/+Qs8Hg/OPffchP/mpJNOQlFREZ599tk+t9NZrVZMmTIFL7zwAo455hjk5+dj2rRpmDZtGh577DGccsopmD59Oq655hpMmDABTU1N2Lx5Mz7//HN8/PHHgx+8Hn7wgx/goYcewr333ovnn39+0OPWXwOd+0ebo4OhKAruvPNOXHfddTj99NNx0UUXoba2FqtXr0ZlZWW/VqgefPBB7Ny5E9///vfxxhtvxFbC1q5diz//+c+YP39+ryLjV199Ne69915cffXV+PKXv4y///3v2L17d6+2B/I7uydZlgf992r37t0444wzcNFFF2HKlCkwGo145ZVX0NTUhEsuuSTu2jfffBNjx45lyntKraFO60g0kq1Zs0ZceeWVYtKkScLhcAhFUURVVZW47rrrRFNTU6/rn3rqKfGlL31JmM1mkZeXJ+bPnx9LQy2EEBs3bhQnnXSSsFqtYvTo0bHU6uhRNLOzs1NcdtllIjc3V+BwYeioP//5z7EiteiRovjf//63OO+880RBQYEwm81i3Lhx4qKLLhLr16+PXZMo7fWR9FUYuqe+Uia/9dZbYu7cucJqtYqcnBxxzjnnxBWGjrrnnntEWVmZkGW5XynwX3jhhdhY5+fn9yoMLcTA0t4P5LlGt4LB0ULOX/rSl3oVPhVCiKamJnHttdeK8vJyYTKZRGlpqTjjjDPEr3/967jrfD6f+PGPfyzGjx8fu+6CCy4Qe/fuPWrfhRDi008/FVdeeaWorKwUFotF5Ofni9NOO0289dZbva492jwVoivV96RJk4TJZBIlJSVi2bJlfRaGTkRVVfHzn/9cTJ06NfZzZs2aJe666y7hdrv79Zh+/OMfCwCiqqqq131btmwRl156qRg7dqwwm82iuLhYnH322XGlCPpypH53F32e+7qvZ5r4zz77TFxxxRWiqKhImM1mMWHCBHHttdfGpTf3eDzi1ltvFVVVVUJRFFFYWChOPvlk8b//+799Fnzu7rjjjhNXXXVV7PtzzjlHWCyWhEWKo5YsWSJMJpM4dOhQn6//TZs2iVmzZglFUXo9tr1794orrrhClJaWCpPJJMrKysTZZ58t/vjHP8auGchrTYi+C0N377PBYIgVRu/PuPXVZl+/w/rqc3/mftSR5qgQfae979mXvn5/Pvzww2LcuHHCbDaLE044QWzcuFHMmjVLfPWrX03483oKBoPiwQcfFLNmzRJ2u13YbDYxc+ZM8dBDDyWcbz6fT1x11VXC5XIJp9MpLrroItHc3Jxwvvf1O7u/haEH8/fq0KFD4tprrxWTJk0SdrtduFwuceKJJ4oXX3wx7rpIJCJGjRolbrvttn6NF1F/SUKk6MQnERElRZIkXHvttQm3GBLp6ZlnnsG1116L/fv3xxWwppFB0zQUFRXhvPPOS7glmOK9+uqruOyyy7B3716MGjUq3d2hYYRnyIiIiEaoyy+/HGPHjk2YwIOGl0Ag0GtL++9+9zu0trbi1FNPTU+nsszPf/5zLF++nMEYpRzPkBERjTCtra1QVbXP+w0GQ581mmh4kWX5qNkcaXh47733cOONN+LCCy9EQUEBtmzZgt/+9reYNm0aLrzwwnR3Lyts3rw53V2gYYoBGRHRCHPeeefh3Xff7fP+cePGoba2dug6RES6q6ioQHl5OR5++GG0trYiPz8fV1xxBe69995exdiJaGjxDBkR0Qjz4YcfHjHVtdVqxdy5c4ewR0RERCMXAzIiIiIiIqI0YVIPIiIiIiKiNOEZshTRNA319fVwOp39KrBIRERERETDkxACHo8Ho0ePhiwfeQ2MAVmK1NfXo7y8PN3dICIiIiKiDFFXV4cxY8Yc8RoGZCnidDoBdA16Tk5OmntDRERERETp0tHRgfLy8liMcCQMyFIkuk0xJyeHARkREREREfXrKBOTehAREREREaUJAzIiIiIiIqI0YUBGRERERESUJgzIiIiIiIiI0oQBGRERERERUZowICMiIiIiIkoTBmRERERERERpwoCMiIiIiIgoTRiQERERERERpQkDMiIiIiIiojRhQEZERERERJQmDMiIiIiIiIjShAEZERERERFRmhjT3QEiIiIiIjo6TRM40O6HVw3DrhhRlmuFLEtZ0z4lxoCMiIiIiCjD1TR7sHZbE/Ye7EQgHIHFaEBlkQPV00pQVezM+PapbwzIiIiIiIgyWE2zB6s21qLVq2KUywKbYoVPDWNbvRv1bj+Wzq0YVNCkd/t0ZDxDRkRERESUoTRNYO22JrR6VUwsdsBpMcEgS3BaTJhY7ECrV8W67U3QNJGR7dPRMSAjIiIiIspQB9r92HuwE6NcFkhS/HkuSZIwymVBTXMnDrT7M7J9OjoGZEREREREGcqrhhEIR2BTEp80sioGBMMReNVwRrZPR8eAjIiIiIgoQ9kVIyxGA3x9BER+NQKz0QB7HwFVutuno2NARkRERESUocpyragscqDBHYAQ8ee4hBBocAdQVexAWa41I9uno2NARkRERESUoWRZQvW0EuTbFexp7oQnEEJY0+AJhLCnuRP5dgULppYkXS9M7/bp6CTRMxSmpHR0dMDlcsHtdiMnJyfd3SEiomGGBVuHp2x+XsNhDVvq2tDiVVFgVzCzPA9GIz/r10tNswevf1yPDTub0REII8dixOmTirHo+NEpr0MWDHdtU6wqdmDB1OyoQ5Zpr6WBxAZp3Qx655134q677oq77dhjj8XOnTsBAIFAADfffDOef/55BINBVFdX4/HHH0dJSUns+v3792PZsmV4++234XA4sHjxYqxYsQJG4xcP7Z133sFNN92E7du3o7y8HLfddhuWLFkS93Mfe+wx3HfffWhsbMTxxx+PRx55BCeccIJ+D56IiKifWLB1eMrm53X9jias3liL2hYvQhENJoOMigI7lsytwBmTS47eAA3Ynz+qx+821cITCEMAkADUtvgQFsDNC44ddPtVxU5MONWhW1CjZ8CUza8lIAMKQ0+dOhVvvfVW7PvugdSNN96I119/HS+99BJcLheWL1+O8847Dxs3bgQARCIRLFq0CKWlpdi0aRMaGhpwxRVXwGQy4Wc/+xkAYN++fVi0aBG+973v4dlnn8X69etx9dVXY9SoUaiurgYAvPDCC7jpppuwcuVKnHjiiXjooYdQXV2NXbt2obi4eAhHg4iIKB4Ltg5P2fy8rt/RhBVrdsITCKHArsCqGOBXI9jd7MGKNV0fqjMoS6371+3Cynf3IqwJKAYJBhmIaEBHMIyV7+4FkJqgTJYllOfbBt1OT3oGTNn8WopK65bFO++8E6+++io++uijXve53W4UFRXhueeewwUXXAAA2LlzJyZPnozNmzfjpJNOwpo1a3D22Wejvr4+tmq2cuVK3HLLLTh48CAURcEtt9yC119/Hdu2bYu1fckll6C9vR1vvPEGAODEE0/E7Nmz8eijjwIANE1DeXk5rrvuOvzoRz/q12PhlkUiIko1TRN44p292FbvxsRiR1yNICEE9jR3YnqZC9+bX5k129wou5/XcFjD0tXvY3ezB2PzrJDlL7YoapqG/W1+HFvixFOLZ3P7YooEAmGceO8GdARDsBmlXmPuCwu4LCa8d8vpsFjSvtbSS++AyQifGkaDO4B8uzKogCmTX0sDiQ3S/krZs2cPRo8ejQkTJuDyyy/H/v37AQAffvghQqEQzjzzzNi1kyZNwtixY7F582YAwObNmzF9+vS4LYzV1dXo6OjA9u3bY9d0byN6TbQNVVXx4Ycfxl0jyzLOPPPM2DWJBINBdHR0xH0RERGlEgu2Dk/Z/LxuqWtDbYsXBXYlLjAAut4/FdgV7DvkxZa6tjT1cPh5Yct+dAZDUGQp4ZgrsgRPIIQXtuxPUw/7pmkCa7c1odWrYmKxA06LCQZZgtNiwsRiB1q9KtZtb4KmJbc+lM2vpe7SGpCdeOKJWL16Nd544w088cQT2LdvH+bNmwePx4PGxkYoioLc3Ny4f1NSUoLGxkYAQGNjY1wwFr0/et+Rruno6IDf78ehQ4cQiUQSXhNtI5EVK1bA5XLFvsrLy5MaAyIior6wYOvwlM3Pa4tXRSiiwaoYEt5vVQwIRTS0eNUh7tnwdaAtAE0Ahj7etRtkQBNd12UavQOmbH4tdZfWdc2FCxfG/vu4447DiSeeiHHjxuHFF1+E1ZrZtQ5uvfVW3HTTTbHvOzo6GJQREVFKdS/Y6rSYet3Pgq3ZKZuf1wK7ApNBhl+NwGnpHSH41QhMhq6VMkqNsjwLZKnrzFiioCyiAbLUdV2m+SJgSvy+3qoY0NQRSDpgyubXUndp37LYXW5uLo455hjU1NSgtLQUqqqivb097pqmpiaUlpYCAEpLS9HU1NTr/uh9R7omJycHVqsVhYWFMBgMCa+JtpGI2WxGTk5O3BcREVEqsWDr8JTNz+vM8jxUFNjR4lWhaVrcfZrWtTI2vtCOmeV5aerh8HPxzLFwmE1QNZFwzFVNwGkx4eKZY9PUw751D5gSGWzAlM2vpe4yKiDr7OzE3r17MWrUKMyaNQsmkwnr16+P3b9r1y7s378fc+bMAQDMmTMHW7duRXNzc+yaN998Ezk5OZgyZUrsmu5tRK+JtqEoCmbNmhV3jaZpWL9+fewaIiKidGDB1uEpm59Xo1HGkrkVcFpM2N/mj+v7/jY/ciwmLD65ggk9UshiMeKKk8fBKEvwhQXUsIaIpkENdyX0MMkSvj1nXEYm9NA7YMrm11J3ac2y+MMf/hDnnHMOxo0bh/r6etxxxx346KOP8Mknn6CoqAjLli3D3/72N6xevRo5OTm47rrrAACbNm0C0JX2fsaMGRg9ejR+8YtfoLGxEd/+9rdx9dVXx6W9nzZtGq699lpceeWV2LBhA66//nq8/vrrcWnvFy9ejF/96lc44YQT8NBDD+HFF1/Ezp07e50t6wuzLBIRkV6yvWArJZbNz2uiOmTjC+1YfDLrkOnl/nW78LtNn6EzGIImurYpOi0mfHvOuJSkvNdLzyyL0TIJqciy2P1nZNpraSCxQVoDsksuuQR///vf0dLSgqKiIpxyyin46U9/isrKSgBfFIb+wx/+EFcYuvtWws8++wzLli3DO++8A7vdjsWLF+Pee+/tVRj6xhtvxCeffIIxY8bgJz/5Sa/C0I8++misMPSMGTPw8MMP48QTT+z3Y2FARkREetKzqCqlTzY/r+Gwhi11bWjxqiiwK5hZnseVMZ35fCH8etNefN4awJh8C75zciVstt5npzLNUARMmfZaypqAbDhhQEZEREREetGzuPJQyLSASW8DiQ0yb7MpERERERHF9C6ubIVPDWNbvRv1bn9Ktv3pTZYllOfb0t2NjMR1ZSIiIiKiDKV3cWVKPwZkREREREQZSu/iypR+DMiIiIiIiDLUF8WVE580sioGBMORpIsrU/oxICMiIiIiylB6F1em9GNARkRERESUofQurkzpx4CMiIiIiChDybKE6mklyLcr2NPcCU8ghLCmwRMIYU9zJ/LtChZMLRnWKeSHO65tEhERka5GWv0holSrKnZi6dwKvLG1EVsPuOELhWEzGXHcGBeqp5VmfMp7OjIGZERERKSbbC9mS5RRpMNfh/+bie6HBwZkREREpIvhUMyWKBN0fy2V5VphU4zwqWFsr+9AgzvA11KW4xkyIiIiSjkWsyVKDb6Whj8GZERERJRyLGZLlBp8LQ1/DMiIiIgo5VjMlig1+Foa/hiQERERUcqxmC1RavC1NPwxICMiIqKUYzFbotTga2n4Y0BGREREKcditkSpwdfS8CeJnqE2JaWjowMulwtutxs5OTnp7g4REVFG6F6HLBju2lpVVezAgqmsQ0Y0EHwtZZeBxAbcbEpERES6qSp2YsKpDhxo98OrhmFXjCjLtfLTfBq2NE3oMt+rip2o+IodW+ra0OJVUWBXMLM8D0Zjdmx402tchgMGZERERKQrWZZQnm9LdzeIdNd9FSsQjsBiNKCyyIHqaYNfxUrU9vv72lLStt70HJfhgAEZEREREdEg1TR7sGpjLVq9Kka5LLApVvjUMLbVu1Hv9mPp3Iqkgw8929ZbNvd9qGTHGicRERERUYbSNIG125rQ6lUxsdgBp8UEgyzBaTFhYrEDrV4V67Y3QdMGnrpBz7b1ls19H0oMyIiIiIiIBuFAux97D3ZilMsCSYo/FyVJEka5LKhp7sSBdn9Gta23bO77UGJARkREREQ0CF41jEA4AlsfxZmtigHBcATePoo7p6ttvWVz34cSAzIiIiIiokGwK0ZYjAb4+ggs/GpXmnp7H4FJutrWWzb3fSgxICMiIiIiGoSyXCsqixxocAfQs8SvEAIN7gCqih0oy7VmVNt6y+a+DyUGZEREREREgyDLEqqnlSDfrmBPcyc8gRDCmgZPIIQ9zZ3ItytYMLUkqbpberatt2zu+1CSRM9wlZIykGrcRERERDT8dK+3FQx3bcerKnZgwdTU1iFLddt6y+a+J2sgsQEDshRhQEZERJQemiZwoN0PrxqGXTGiLNc64j9xpyPTc85ka9t6y+a+J2MgscHIPkFHREREWa37J++BcAQWowGVRQ5UTxu+n7zT4Og9Z2RZQnm+LQU9Hdq29ZbNfdcbAzIiIiLKSjXNHqzaWItWr4pRLgtsihU+NYxt9W7Uu/1YOreCQRnF4ZyhTMSkHkRERJR1NE1g7bYmtHpVTCx2wGkxwSBLcFpMmFjsQKtXxbrtTdA0nsygLpwzlKkYkBEREVHWOdDux96DnRjlskCS4s+hSJKEUS4Lapo7caDdn6YeUqbhnKFMxYCMiIiIso5XDSMQjsDWR0FZq2JAMByBt4+CtDTycM5QpmJARkRERFnHrhhhMRrg6+PNs1/tSq1t7+PNN408nDOUqRiQERERUdYpy7WissiBBncAPSv4CCHQ4A6gqtiBslxrmnpImYZzhjIVAzIiIiLKOrIsoXpaCfLtCvY0d8ITCCGsafAEQtjT3Il8u4IFU0uGdZ0jGhjOGcpULAydIiwMTURE2Sxbi7Z2rykVDHdtOasqdmDB1OyoQ5at4643PcelptmDN7Y2YusBN3yhMGwmI44b40L1tNKUzBkWhiaAhaGJiIhoALK5uHJVsRMTTnVk5ZvUbB53PQ3JuEiHvw7/d6pWJ/TsO+fL8MUVshThChkREWWj3oVyjfCpYTS4A8i3KyyUqxOOe2J6j4ue7Wdr26SPgcQGPENGREQ0QrFQbnpw3BPTe1z0bD9b26bMwICMiIhohGKh3PTguCem97jo2X62tk2ZgQEZERHRCMVCuenBcU9M73HRs/1sbZsyAwMyIiKiEYqFctOD456Y3uOiZ/vZ2jZlBgZkREREIxQL5aYHxz0xvcdFz/aztW3KDAzIiIiIRigWyk0Pjntieo+Lnu1na9uUGZj2PkWY9p6IiLJVthdXzlYc98T0Hhc928/Wtin1BhIbMCBLEQZkRMOPpomsLDZLlAw95ztfS33j2CSm97hk63znfMkeA4kNePqPiCiB7p9EBsIRWIwGVBY5UD2Nn0TS8CTLEsrzbSlvl6+lI9Nr3LOd3uOiZ/t8TmmgGJAREfVQ0+zBqo21aPWqGOWywKZY4VPD2FbvRr3bj6VzK/hGkqgf+FoiSh1+uDF8MakHEVE3miawdlsTWr0qJhY74LSYYJAlOC0mTCx2oNWrYt32Jmgad3sTHQlfS0SpE/1wY1u9G7k2EyYUOpBrM2FbvRurNtaiptmT7i7SIDAgIyLq5kC7H3sPdmKUywJJit+XL0kSRrksqGnuxIF2f5p6SJQd+FoiSg1+uDH8MSAjIurGq4YRCEdg66PAplUxIBiOwNtHgU4i6sLXElFq8MON4Y8BGRFRN3bFCIvRAF8fbxL9aleqYXsfbzKJqAtfS0SpwQ83hj8GZERE3ZTlWlFZ5ECDO4CeVUGEEGhwB1BV7EBZrjVNPSTKDnwtEaUGP9wY/hiQERF1I8sSqqeVIN+uYE9zJzyBEMKaBk8ghD3Nnci3K1gwtYR1X4iOgq8lotTghxvDH0NpIqIeqoqdWDq3IpZeuKkjALPRgOllLiyYyvTCRP3F19LwxgLIiYXDGrbUtaHFq6LArmBmeR6MxuTXQKIfbtS7/djd1AmnxQiDLCGiCXgCYRQ4UvfhBp/T9JBEz1CbkjKQatxElB34x4MoNfhaGn70rImVzfW21u9owuqNtaht8SIU0WAyyKgosGPJ3AqcMbkkY9sG+Jym2kBiA66QERH1QZYllOfb0t0NoqzH19LwomfB72wuJr5+RxNWrNkJTyCEArsCq2KAX41gd7MHK9bsBICkA6eaZg827GyG3WzASRPyYZBlRDQNnkAYG3Y2Y1yBbVDjwuc0vXiGjIiIiIj6Rc+aWNlcbysc1rB6Yy08gRDG5lnhtJhglGU4LSaMzbPCEwjh6U21CIe1AbfdfVyOKXFidK4NJTkWjM614ZgS56DHhc9p+jEgIyIiIqJ+0bMmVjbX29pS14baFi8K7ApkOf7ttSzLKLAr2HfIiy11bQNuW+9x4XOafgzIiIiIiKhf9KyJlc31tlq8KkIRDVbFkPB+q2JAKKKhxasOuG29x4XPafoxICMiIiKiftGzJlY219sqsCswGWT41UjC+/1qBCZD10rZQOk9LnxO048BGRERERH1i541sbK53tbM8jxUFNjR4lWhafHnxDSta2VsfKEdM8vzBty23uPC5zT9GJARERERUb/oWfA7m4uJG40ylsytgNNiwv42f1zf97f5kWMxYfHJFUnVI9N7XPicph/rkKUI65ARERHRSNG9rlQw3LXtrKrYkZKC33q2rbdEtcLGF9qx+OTB1wrTe1z4nKbWQGIDBmQpwoCMiIiIRhI9C35nczFxVY1g3c5GNLqDKHWZsWBSKZQ+kn0MlN7jwuc0dVgYmoiIiIh0pWfB72wtJt59JSgQjsBiNOCzQ35UT0vNSpDe48LnND0YkBERERHRiBIOa9hS14YWr4oCu4KZ5XlJne/qrqbZg1Uba9HqVTHKZYFNscKnhrGt3o16tx9L51YM2+15NDgMyIiIiIhoxEh0zquiwI4lc5M/56VpAmu3NaHVq2JisSNWBNlpMcFhNmJPcyfWbW/ChELHsN6mR8lhQEZEREREI8L6HU1YsWYnPIEQCuwKrIoBfjWC3c0erFizEwCSCsoOtPux92AnRrkssWAsSpIkjHJZUNPciQPtfm7bo16Y9p6IiIiIhr1wWMPqjbXwBEIYm2eF02KCUZbhtJgwNs8KTyCEpzfVIhzWjt5YD141jEA4AlsfBY6tigHBcATePgok08jGgIyIiIiIhr0tdW2obfGiwK5AluPfAsuyjAK7gn2HvNhS1zbgtu2KERajAb4+Ai6/2pXq3d5HwNZfmiZQ1+rDzsYO1LX6oGlMlj4ccMsiEREREQ17LV4VoYgGax8p6K2KAa1eFS1edcBtl+VaUVnkwLZ6NxxmY9y2RSEEGtwBTC9zoSzXmnT/E2VwrCxypCyDI6UPV8iIiIiIaNgrsCswGWT41UjC+/1qBCZD10rZQMmyhOppJci3K9jT3AlPIISwpsETCGFPcyfy7QoWTC1JOqFHNIPjtno3cm0mTCh0INdmwrZ6N1ZtrEVNsyepdikzMCAjIiIiomFvZnkeKgrsaPGq0DQNwVAEPjWMYCgCTdPQ4lUxvtCOmeV5SbVfVezE0rkVmDbahXZfCLWHvGj3hTC9zDWolPc9Mzg6LSYYZAlOiwkTix1o9apYt72J2xezGLcsEhEREdGwZzTKWDK3Ane99gl2NHpgkCRIEiAEEBECBXYzFp9cMah6ZFXFTkw41YED7X541TDsihFludZBpbpnBsfhjwEZEREREY0I4wpsGF9ogzcYRjAcgdAEJEmC2WhARaEN4woGH9DIspTSwOiLDI6Jz59ZFQOaOgLM4JjFGJARERER0bAX3fpnU4y4dPYYNHYE4QtFYDMZUJpjxt5Dvows3tw9g6PTYup1f6oyOFL68JkjIiIiomGv+9Y/g8GAsrz4VaxM3fo3FBkcKb2Y1IOIiIiIhr1sLd6sdwZHSj8GZEREREQ07A1V8WY96JXBkTJD5s04IiIiIqIUy/atf3pkcKTMwICMiIiIiIa96Na/ercfe5q7zpJZFQP8agQN7kBWbP1LdQZHygzcskhEREREIwK3/lEm4goZERFRFtA0wa1KNCB6zxk92+/0qrh/wy583hrAmHwLbj79WDjsSkrazuatf/w9MDxlTEB277334tZbb8UPfvADPPTQQwCAQCCAm2++Gc8//zyCwSCqq6vx+OOPo6SkJPbv9u/fj2XLluHtt9+Gw+HA4sWLsWLFChiNXzy0d955BzfddBO2b9+O8vJy3HbbbViyZEncz3/sscdw3333obGxEccffzweeeQRnHDCCUPx0ImIiI6optmDtduasPdgJwLhCCxGAyqLHKieVsJP9CkhveeMnu0vf24L1mxtQER8cdvvNu3Hwumj8OhlMwfZ8y7ZuPWPvweGr4zYsvj+++/jV7/6FY477ri422+88Ua89tpreOmll/Duu++ivr4e5513Xuz+SCSCRYsWQVVVbNq0CU8//TRWr16N22+/PXbNvn37sGjRIpx22mn46KOPcMMNN+Dqq6/G2rVrY9e88MILuOmmm3DHHXdgy5YtOP7441FdXY3m5mb9HzwREdER1DR7sGpjLbbVu5FrM2FCoQO5NhO21buxamMtapo96e4iZRi954ye7S9/bgv++p/4YAwAIgL4638asPy5LYPqe7bi74HhLe0BWWdnJy6//HI8+eSTyMvLi93udrvx29/+Fg888ABOP/10zJo1C6tWrcKmTZvw3nvvAQDWrVuHTz75BL///e8xY8YMLFy4EPfccw8ee+wxqKoKAFi5ciXGjx+P+++/H5MnT8by5ctxwQUX4MEHH4z9rAceeADXXHMNli5diilTpmDlypWw2Wx46qmnhnYwiIiIutE0gbXbmtDqVTGx2AGnxQSDLMFpMWFisQOtXhXrtjdB08TRG6MRQe85o2f7nV4Va7Y2xL6XpS++otZsbUCnV02q79mKvweGv7QHZNdeey0WLVqEM888M+72Dz/8EKFQKO72SZMmYezYsdi8eTMAYPPmzZg+fXrcFsbq6mp0dHRg+/btsWt6tl1dXR1rQ1VVfPjhh3HXyLKMM888M3ZNIsFgEB0dHXFfREREqXSg3Y+9B7uywXVP0Q0AkiRhlMuCmuZOHGj3p6mHlGn0njN6tn//hl2xlbGex6Ki30dE13UjCX8PDH9pDcief/55bNmyBStWrOh1X2NjIxRFQW5ubtztJSUlaGxsjF3TPRiL3h+970jXdHR0wO/349ChQ4hEIgmvibaRyIoVK+ByuWJf5eXl/XvQRERE/eRVwwiEI7D1UajWqhgQDEfg7aPQLY08es8ZPdv/vDWQ0uuGC/4eGP7SFpDV1dXhBz/4AZ599llYLJZ0dSNpt956K9xud+yrrq4u3V0iIqJhxq4YYTEa4OvjjZZfjcBsNMDexxs1Gnn0njN6tj8mv3/vB/t73XDB3wPDX9oCsg8//BDNzc2YOXMmjEYjjEYj3n33XTz88MMwGo0oKSmBqqpob2+P+3dNTU0oLS0FAJSWlqKpqanX/dH7jnRNTk4OrFYrCgsLYTAYEl4TbSMRs9mMnJycuC8iIqJUKsu1orLIgQZ3AELEnw8RQqDBHUBVsQNludY09ZAyjd5zRs/2bz79WBgO78jreRwq+r1B6rpuJOHvgeEvbQHZGWecga1bt+Kjjz6KfX35y1/G5ZdfHvtvk8mE9evXx/7Nrl27sH//fsyZMwcAMGfOHGzdujUuG+Kbb76JnJwcTJkyJXZN9zai10TbUBQFs2bNirtG0zSsX78+dg0REVE6yLKE6mklyLcr2NPcCU8ghLCmwRMIYU9zJ/LtChZMLWEdIorRe87o2b7DrmDh9FGx7zXxxVfUwumjUlaPLFvw98DwJ4meoXYanXrqqZgxY0asDtmyZcvwt7/9DatXr0ZOTg6uu+46AMCmTZsAdKW9nzFjBkaPHo1f/OIXaGxsxLe//W1cffXV+NnPfgagK+39tGnTcO211+LKK6/Ehg0bcP311+P1119HdXU1gK6094sXL8avfvUrnHDCCXjooYfw4osvYufOnb3OlvWlo6MDLpcLbrebq2VERJRS3esPBcNd25Oqih1YMJX1hygxveeMnu0nqkNmkJDSOmTZqKbZgze2NmLrATd8oTBsJiOOG+NC9bRS/h7IQAOJDTJ6s+mDDz4IWZZx/vnnxxWGjjIYDPjrX/+KZcuWYc6cObDb7Vi8eDHuvvvu2DXjx4/H66+/jhtvvBG//OUvMWbMGPzmN7+JBWMAcPHFF+PgwYO4/fbb0djYiBkzZuCNN97odzBGRESkp6piJyac6sCBdj+8ahh2xYiyXCs/Eac+6T1n9Gz/hjMnYkK+Da9va4AnEIbTYsSiaaNw7syyFPQ8uwkA/lAE3mAEEqReWzspO2XUClk24woZERER0eBECyC3elWMcllgU4zwqWE0uAPItytYOrdiRK4G1TR78NBbe7C70YOIEOgKzSQYJAnHlDpxw5kTR+S4ZLKBxAZpr0NGRERERMQCyIlpmsBz/9qPj+vaEdE0OC1G5NvNcFqMiGgaPq5rx3P/2j/ixmU4YUBGRERERGnHAsiJfd7mw3uftsAgAQUOM8xGA2RJgtloQIHDDFkC/vVpCz5v86W7q5QkBmRERERElHYsgJzYp4e8cPtCyLGZEgaqLpsJ7f4QPj3kTVMPabAYkBERERFR2rEAct+EBEjoK2EKk/tkOwZkRERERJR2LICc2PhCO3KtCtp9oYTj4vaF4LIqGF9oT1MPabAYkBERERFR2rEAcmLleTacND4fmhBo8aoIhiPQhEAwHEGLV4UmBOZMyEd5ni3dXaUkjbw1XyIiIiLKSFXFTiydWxErOt3UEYDZaMD0MteILYQuyxIuO2ksmjuD2N3kgSfwxZZOgyzh+PJcXHri2BEXqA4nrEOWIqxDRkRERAMVDmvYUteGFq+KAruCmeV5MBpTs4FJ00TWFhNX1QjW7WxEozuIUpcZCyaVQlEMKWtfz7HRq+2aZg/e2NqIrQfc8IXCsJmMOG6MC9XTSkdkoJrpBhIbMCBLEQZkRERENBDrdzRh9cZa1LZ4EYpoMBlkVBTYsWRuBc6YXDKotmuaPbFVpkA4AovRgMoiB6qnZf4qk57jAug7NnqPezYH2SPNQGIDblkkIiIiGmLrdzRhxZqd8ARCKLArsCoG+NUIdjd7sGLNTgBIOvioafZg1cZatHpVjHJZYFOs8KlhbKt3o97tx9K5FRkblOk5LoC+YzMU4y7LEsrzeVZsuGFSDyIiIqIhFA5rWL2xFp5ACGPzrHBaTDDKMpwWE8bmWeEJhPD0plqEw9qA29Y0gbXbmtDqVTGx2AGnxQSDLMFpMWFisQOtXhXrtjdB0zJvg5Se4wLoOzbZPO6UfgzIiIiIiIbQlro21LZ4UWBXIMvxb8VkWUaBXcG+Q15sqWsbcNsH2v3Ye7ATo1yWhEWER7ksqGnuxIF2/6Aegx70HBdA37HJ5nGn9GNARkRERDSEWrwqQhEN1j6SVFgVA0IRDS1edcBte9UwAuEIbH0UT7YqBgTDEXj7KL6cTnqOC6Dv2GTzuFP6MSAjIiIiGkIFdgUmgwy/Gkl4v1+NwGToWhEaKLtihMVogK+PN/5+NQKz0QB7H4FDOuk5LoC+Y5PN407px4CMiIiIaAjNLM9DRYG9q6ivFn8eStO6VoDGF9oxszxvwG2X5VpRWeRAgzuAnom0hRBocAdQVexAWa51UI9BD3qOC6Dv2GTzuFP6MSAjIiIiGkJGo4wlcyvgtJiwv80PTyCEsKbBEwhhf5sfORYTFp9ckVQ9MlmWUD2tBPl2BXuaO+Pa3tPciXy7ggVTSzIyVbqe4wLoOzbZPO6UfqxDliKsQ0ZEREQDkaje1vhCOxafnNo6ZMFw13a5qmIHFkzNzjpkqRoXQN+x0bt4M+uQZQ/WISMiIiLKcGdMLsH8iUXYUteGFq+KAruCmeV5Sa8AdVdV7MSEUx26vnnXKzjQc1yAIRgb6fDX4f9O1cpHNhf7piPjClmKcIWMiIiIRgoGB731LgxthE8No8EdQL5dSXHR6dS1TfoYSGzAM2RERERE1G/R4GBbvRu5NhMmFDqQazNhW70bqzbWoqbZk+4uDjkWnabBYEBGRERERP3C4CAxFp2mwWBARkRERET9wuAgMRadpsFgQEZERERE/cLgIDEWnabBYEBGRERERP3C4CAxFp2mwWBARkRERET9wuAgMRadpsFgQEZERERE/cLgoG9VxU4snVuBaaNdaPeFUHvIi3ZfCNPLXINOS69n25R+rEOWIqxDRkREetKrCC9RMrrXIQuGu7YpVhU7sGBqauqQZfN8D4c13YpaZ/O4jDQDiQ1G1gZfIiKiLMQivJRpqoqdmHCqQ5fgIJvne6K+v7+vLWV9l2UJ5fm2FPSUMgkDMiIiogwWLcLb6lUxymWBTbHCp4axrd6Neref25UobfQIDrJ5vmdz3ym9eIaMiIgoQ7EIL40k2Tzfs7nvlH4MyIiIiDIUi/DSSJLN8z2b+07px4CMiIgoQ7EIL40k2Tzfh6rvmiZQ1+rDzsYO1LX6uOI2TPAMGRERUYbqXoTXaTH1un+kFuGl4Smb5/tQ9D2bk53QkXGFjIiIKEOxCC+NJNk83/XuezRhyLZ6N3JtJkwodCDXZsK2ejdWbaxFTbMnFQ+D0oQBGRERUYZiEV4aSbJ5vuvZdyYMGf5YGDpFWBiaiIj0oncRXkofFvrtLZvnux59r2v14cE3dyPXZkq4HdITCKHdF8KNZx3DGmUZhIWhiYiIhhE9i/BGMTAYetl+JkivOTMU810vVcVOVHzFji11bWjxqiiwK5hZngejMflNaV8kDLFCCAFPIAw1okExyHBajLAqBjR1BDIy2Qn1DwMyIiKiLKBHEd6obA8MslG2FxHWe87oOd/1lGhc3t/XNqhxiSYMqW/3ocEdRJtPRTiiwWiQkWdTMMplzthkJ9Q/fOaIiIhGsGwPDLJRzzNB0bpVTosJDrMRe5o7sW57EyYUOjJyVYhzJjG9xqUs14pcqwlv7miCYpThtJhgshgRigg0ewL4vM2HBVNKMjLZCfUPk3oQERGNUEwWkB7ZXESYcyYx3cclOk2EABBtQxz+/otbKDsxICMiIhqhsjkwyGbZXACZcyYxPcflQLsf7b4QZlfkoSTHikBIQ7tPRSCkocRlxeyKPLT7QiNuzIcTblkkIiIaobonC0iEyQL0kc0FkDlnEtNzXKJtTyh0YEyerVdSj4gQqD3kHXFjPpxwhYyIiGiE6h4YJJLJgUE2y+YCyJwziek5Lt3bliQJOVYTCh1m5FhNkCRpxI75cMKAjIiIaITK5sAgm2VzAWTOmcT0HBeO+fDHgIyIiGiEyubAINtVFTuxdG4Fpo12od0XQu0hL9p9IUwvc2V0lkLOmcT0HBeO+fAniZ6hNiVlINW4iYiIMklNswdvbGvE1gNu+NQIbIoBx5Xlsg7ZEMjWgtzd620Fw11b5qqKHVgwNTVzJhzWUlpceajoOS56jzml1kBiA242JSIioq682QIQXf/Ta2sU6SNbCyBXFTsx4VSHLsHk+h1NWL2xFrUtXoQiGkwGGRUFdiyZW4EzJpekoPf60XNc9Gyb0osBGRER0QjWvZhtWZ4VNsUInxrG9oYONHQEMnr7HKWXHsHk+h1NWLFmJzyBEArsCqyKAX41gt3NHqxYsxMAUhKU6bkyqWeQna0BPB0ZAzIiIqIRqmcx22j9JKfFBIfZiD3NnVi3vQkTCh38FJ50Fw5rWL2xFp5ACGPzrJDlri2KTosMu2LA/jY/nt5Ui/kTiwa1fbH71r9AOAKL0YDKIge36FLaZP5mXCIiItIFi/xSJtlS14baFi8K7EosGIuSZRkFdgX7Dnmxpa4t6Z8RXRHeVu9Grs2ECYUO5NpM2FbvxqqNtahp9gz2YRANGAMyIiKiEeqLYraJN8xYFQOC4QgLztKQaPGqCEU0WBVDwvutigGhiIYWr5pU+91XhKuK7BACaPOpEAKoKrKj1ati3fYmaNrgzk9qmkBdqw87GztQ1+obdHs0/HHLIhER0QjVveCs02LqdT8LztJQKrArMBlk+NUInJbeawZ+NQKToWulLBnRFWGrScYHn7WjzaciHNFgNMjIsykY5TLHVoSTPafF7ZCUDP6GJSIiGqGiBWe31bvhMBvjti1GC85OL3Ox4CwNiZnleagosGN3swd2xRC3bVHTulbGji1xYmZ5XlLte9UwDnUG0eJVEQxF4LCYYLIYEYoIHPQE0HE4kUiyK8LdE+SMcllgU6zwqWFsq3ej3u1nghzqE7csEhERjVAsOEuZxGiUsWRuBZwWE/a3+ePm4/42P3IsJiw+uSLphB5WkwGHOlV0BsLItyswG2XIkgSzUUa+XUFnIIxDnSqspsRbJo+kZ4Icp8UEgyzBaTFhYrEjZdshaXjiChkREdEIVlXsxNK5FbFtVk0dAZiNBkwvc7HgLA25aEr7aB2yVq8Kk0HGsSVOLD55cHXIuj5WEJDQV1DUdV8yHz8MJEEO09ZTTwzIiIiIRjgWnE0fPeth6S0c1rClrg0tXhUFdgUzy/MGlY4+6ozJJZg/sSjlbftCERQ6zGiRgJbOIBSTAbIkQRMCaigCh8WIArsZvlBkwG1/kSAn8fZeq2JAU0eACXIoIQZkRERExIKzaZDNCSDW72iKrWKFIhpMBhkVBXYsmTu4VawoWZYwymVFjtUEu2JMSZBqV4wodJihGCXsbuzEwU4/IpqAQZaQazVhvMuCHIuSVBIbJsihweCsICIiIhpi2ZwAYv2OJqxYsxOew0kwrIoBfjWC3c0erFizEwAGFZTpFaiW5VqRazXh/dpWKAYZY3KtkGRAaEAwrGFXYycWTClJKokNE+TQYDCpBxEREdEQyuYEEOGwhtUba+EJhDA2zwqnxQSjLMNpMWFsnhWeQAhPb6pFOKwl1b7uhZtjcZKAYpJhU4xQTDJw+FxZsiPOBDk0GAzIiIiIiIbQQBJAZJotdW2obfGiwK7EpaUHAFnuqhG275AXW+raBty23oHqgXY/2n0hzK7IQ0mOFYGQhnafikBIQ4nLitkVeWj3hZIe92iCnGmjXWj3hVB7yIt2XwjTy1wZveJJ6ccti0RERERDKJsTQLR4VYQiGqxK4tTwVsWAVq+KFq864Lb1zlQYHfcJhQ6MybPBEwhDjWhQDDKcFiMiQqD2kHdQ484EOZQMBmREREREQyibE0AU2BWYDDL8agROS++NVn41ApOha6VsoPQOVHuOe441fuz9wXBKxp0JcmiguGWRiIiIaAhFE0A0uAMQIn77XTQBRFWxIyMTQMwsz0NFgR0tXhWaFn9OTNM0tHhVjC+0Y2Z53oDb7h4wJTLYQDWbx52GNwZkREREREMomxNAGI0ylsytgNNiwv42f1zf97f5kWMxYfHJFUnVDNM7YMrmcafhLfPWwomIaETL5kK5lB7ZOGeiCSCi6d2bOgIwGw2YXubCgqmZXYcsmtI+Woes1avCZJBxbIkTi09Ovg5ZNGCqd/uxp7nrLFk0pX6DO5CSgCk67m9sa8TWA2741AhsigHHleVmRf03Gp4YkBERUcbI5kK5lB7ZPGeyOQHEGZNLMH9iEbbUtaHFq6LArmBmeV5SK2PdDVmgKrq+RNf/9FqRIxpKkuAMTImOjg64XC643W7k5OSkuztERFmnd6FcI3xqOPbJONNGU0+cM8OXXquenDM0VAYSG3CFjIiI0q5n/aFoymunxQSH2Yg9zZ1Yt70JEwodWbF6QPrjnBne9MhUyDlDmYpJPYiIKO2yuVAupQfnDA0U5wxlKgZkRESUdl/UH0q8ccOqGBAMRzKyUC6lB+cMDRTnDGUqBmRERJR2etcfouGHc4YGinOGMhUDMiIiSjsWbKWB4pyhgeKcoUzFgIyIiNKOBVtpoDhnaKA4ZyhTMe19ijDtPRHR4HWvKRUMd20fqip2ZHyhXEofzpnhSc9i35wzNBQGEhswIEsRBmRERKmh5xsxGp44Z4aXmmYP3tjaiK0H3PCGwrCbjJhe5sJXp5emLGDSc86Ew1rKC2ZT9mEdMiIiylp61B+i4Y1zZvioafbgobf2YHeTBxHtizWDfS1e7Gzy4IYzJ2b0Ktb6HU1YvbEWtS1ehCIaTAYZFQV2LJlbgTMml6S7e5ShGJARERERUdppmsBz7+3Hx3XtUIwynBYTTAYJoYiAJxDCx3Xt+MO/9uPHi6YMajWr+5bFQDgCi9GAyiIHqqcNbsvi+h1NWLFmJzyBEArsCqyKAX41gt3NHqxYsxMAGJRRQlw/JSIiIqK0q2vz4b19rZAlCQV2BWajDFmSYDbKKLArkCUJmz9tRV2bL+mfUdPswaqNtdhW70auzYQJhQ7k2kzYVu/Gqo21qGn2JNVuOKxh9cZaeAIhjM2zwmkxwSh3BZVj86zwBEJ4elMtwmEt6b7T8MWAjIiIiChNNE2grtWHnY0dqGv1QdNG7tH+fYe8aPeryLWZIEnxK2CSJMFlM8HtV7HvkDep9jVNYO22JrR6VUwsdsBpMcEgS3BaTJhY7ECrV8W67U1JPQdb6tpQ2+LtChzl+LfXstwVUO475MWWurak+k7DG7csEhEREaWBXlvnspkkAIG+AqLBBasH2v3Ye7ATo1yWhAHfKJcFNc2dONDuH/CZxBavilBEg1UxJLzfqhjQ6lXR4lWT7j8NX1whIyIiIhpiem2dy2YTCu1w2Uzo8IUSFm52+0LItZowodCeVPteNYxAOAKbkng9wqoYEAxH4FXDA267wK7AZJDhVyMJ7/erEZgMXStlRD0xICMiIiIaQnpunctmY/JsOGlCASICaOkMIhiOQBMCwXAELZ1BaAI4cUIBxuQll1HTrhhhMRrg6yPg8qtdNcnsfQRsRzKzPA8VBXa0eFVoWvw5MU3T0OJVMb7QjpnleUn1nYY3BmREREREQ2ggW+dGElmWcNmJY3F8eS4MsgxPIIxWbxCeQBgGWcbx5bm47MSxSWdYLMu1orLIgQZ3IOEKXIM7gKpiB8pyrQNu22iUsWRuBZwWE/a3+eEJhBDWNHgCIexv8yPHYsLikytYj4wS4hkyoizAoqc0UNk8Z7K575SY3s+pnoV49ej7F1vnrNA0DQ3uAHyhCGwmA0a5LLAqBjR1BJLaOtdda4cfN/7xY9S3BzA614IHLzge+TkDDzb6oqoRrNvZiEZ3EKUuMxZMKoXSxxmq/qoqduKGMyfizx9+jlf/Uw9vMAy72YhvHj8a584cM6izdbIsoXpaCerdfuxq9MAgS9CEgCxJiGgChU4zFkwtSfr5jaa0f+qfn2J3cydCYQ0mo4xji51Yesr4lKS8Z9Hp4WlQAZmqqti3bx8qKythNA68qSeeeAJPPPEEamtrAQBTp07F7bffjoULFwIAAoEAbr75Zjz//PMIBoOorq7G448/jpKSLyb0/v37sWzZMrz99ttwOBxYvHgxVqxYEdefd955BzfddBO2b9+O8vJy3HbbbViyZElcXx577DHcd999aGxsxPHHH49HHnkEJ5xwwsAHhSjFeOibBiqb50w2950S0/s51bMQr159j26d29noxu7GTrT7Q4hoAgZZQq7VhGNKHcixKEltnYta9PDfsb3+i3Noe5q9mPmzDZg62onXr/9K0u1GPbO5Fr/5xz4c9AQQEQIGScJ9zt24et54fHtOxaDafuitPViztQGRw4tYrb4wHnv3U3za6sejl80cVNtVxU5MKnXiN3sOxfW9yGnB1RMLUzInJUiHk5N0JSlJFRadHr6SCql9Ph+uuuoq2Gw2TJ06Ffv37wcAXHfddbj33nv73c6YMWNw77334sMPP8QHH3yA008/HV//+texfft2AMCNN96I1157DS+99BLeffdd1NfX47zzzov9+0gkgkWLFkFVVWzatAlPP/00Vq9ejdtvvz12zb59+7Bo0SKcdtpp+Oijj3DDDTfg6quvxtq1a2PXvPDCC7jppptwxx13YMuWLTj++ONRXV2N5ubmZIaHKGV46JsGKpvnTDb3nRLT+zmNFuLd3eyB02JEWZ4VTosxVoh3/Y6mjOx715Y4gc17W9HiVaEYZeRYjFCMMlq8KjbvbQUgkto6B/QOxrrbXu/Boof/nnTfga5g7L61u9DY4YfZZECezQSzyYDGDj/uW7sLz2yuTbrt5c9twV//80UwFhURwF//04Dlz20ZVN/X72jC05s/QyAUQVmeFROKHCjLsyIQiuDpzZ8Nas5E5+Oeg50odJpRVexAodOMPQc7Bz0f9ZzrlH5JBWS33norPv74Y7zzzjuwWCyx288880y88MIL/W7nnHPOwde+9jVMnDgRxxxzDH7605/C4XDgvffeg9vtxm9/+1s88MADOP300zFr1iysWrUKmzZtwnvvvQcAWLduHT755BP8/ve/x4wZM7Bw4ULcc889eOyxx6CqXWlFV65cifHjx+P+++/H5MmTsXz5clxwwQV48MEHY/144IEHcM0112Dp0qWYMmUKVq5cCZvNhqeeeiqZ4SFKCR76poHK5jmTzX2nxPR+TvUsxKt33zVN4LMWHzQhYDJIMMgSJKnr/02Grm10+5OsSdba4e8zGIvaXu9Ba0dy59NUNYLf/GMfguEI8m0m2BQDDLIMm2JAvs2EYDiC3/5zH9Q+sg0eSadXxZqtDbHvZemLr6g1WxvQmWTq+Lg5k29Fvt2MHIsJ+XYzxuYPbs7oOR9ZdHr4Syoge/XVV/Hoo4/ilFNOiTuMOnXqVOzduzepjkQiETz//PPwer2YM2cOPvzwQ4RCIZx55pmxayZNmoSxY8di8+bNAIDNmzdj+vTpcVsYq6ur0dHREVtl27x5c1wb0Wuibaiqig8//DDuGlmWceaZZ8auSSQYDKKjoyPuiyiVeOibBiqb50w2950S0/s51bMQ71D0vdkTxOhcCxxmE8IRAX8ognBEwGExYXSuBU0dwaT6fuMfP07pdT2t29mIg54AbIox4bjbFCOaOwJYt7NxwG3fv2FXbGWs5zGu6PcR0XVdMvScM9naNmWGpAKygwcPori4uNftXq+31y+uo9m6dSscDgfMZjO+973v4ZVXXsGUKVPQ2NgIRVGQm5sbd31JSQkaG7te5I2NjXHBWPT+6H1HuqajowN+vx+HDh1CJBJJeE20jURWrFgBl8sV+yovLx/Q4yY6Gj3rpdDwlM1zJpv7Tonp/Zz2pxBvKKIlVYh3qPqea1MwOteC8jwrxuRZUZ5nxWiXBbk2Jem+17cHUnpdT43uICJCwGxM/H7PbJQQEQKN7uCA2/68tX996u91Pek5Z7K1bcoMSQVkX/7yl/H666/Hvo8GYb/5zW8wZ86cAbV17LHH4qOPPsK//vUvLFu2DIsXL8Ynn3ySTLeG1K233gq32x37qqurS3eXaJjRs14KDU/ZPGeyue+UmN7PqZ6FeIey75IkwWwywKYYYTYZIEnSoPo+Otdy9IsGcF1PpS4zDJKEYDjxdspguCtJRqnLPOC2x+T3r0/9va4nPedMtrZNmSGpgOxnP/sZ/vu//xvLli1DOBzGL3/5SyxYsACrVq3CT3/60wG1pSgKqqqqMGvWLKxYsQLHH388fvnLX6K0tBSqqqK9vT3u+qamJpSWlgIASktL0dTU1Ov+6H1HuiYnJwdWqxWFhYUwGAwJr4m2kYjZbEZOTk7cF1Eq6VkvhYanbJ4z2dx3Skzv51TPQrzZ3PcHLzg+pdf1tGBSKYqcFvjUcMK++9QwinMsWDCp7/dQfbn59GNhOLzw1vP4XPR7g9R1XTL0HPdsbZsyQ1IB2SmnnIKPPvoI4XAY06dPx7p161BcXIzNmzdj1qxZg+qQpmkIBoOYNWsWTCYT1q9fH7tv165d2L9/f2wVbs6cOdi6dWtcNsQ333wTOTk5mDJlSuya7m1Er4m2oSgKZs2aFXeNpmlYv379gFf7iFIpWi8l365gT3NnXJHJPc2dyLcrg6qXQsNPNs+ZbO47Jab3c6pnId5s7nt+jhVTRx85dfvU0c6k65EpigFXzxsPs9GAVl8IPjWCiKbBp0bQ6gvBYjTgqlPGJ1WPzGFXsHD6qNj3mvjiK2rh9FFwJLkSpOe4Z2vblBkk0fOjnyF06623YuHChRg7diw8Hg+ee+45/PznP8fatWtx1llnYdmyZfjb3/6G1atXIycnB9dddx0AYNOmTQC6EoHMmDEDo0ePxi9+8Qs0Njbi29/+Nq6++mr87Gc/A9CV9n7atGm49tprceWVV2LDhg24/vrr8frrr6O6uhpAV9r7xYsX41e/+hVOOOEEPPTQQ3jxxRexc+fOXmfL+tLR0QGXywW3283VMkqp7nVwguGubTJVxQ4smMq6TJRYNs+ZbO47Jab3c5qoNtP4QjsWn5zaOmTZ1ve+Ut/rWYesOMeCq04ZfB2y5c9tiatDBnStjC2cPmrQdcgAfcc9W9um1BtIbJBUQPa3v/0NBoMhFtBErV27FpqmxQo7H81VV12F9evXo6GhAS6XC8cddxxuueUWnHXWWQC+KAz9hz/8Ia4wdPethJ999hmWLVuGd955B3a7HYsXL8a9997bqzD0jTfeiE8++QRjxozBT37yk16FoR999NFYYegZM2bg4YcfxoknntjvMWFARnrSNIED7X541TDsihFluVauFNARZfOcyea+U2J6P6fhsIYtdW1o8aoosCuYWZ6XstWCbO57a4cfN/7xY9S3BzA614IHLzg+6ZWxRAKBMF7Ysh8H2gIoy7Pg4pljYbGk5pyn3n3Xc9z1bFtVI1i3sxGN7iBKXWYsmFSa1Gok6U/3gOy4447Dvffei6997Wtxt7/xxhu45ZZb8PHHyaVSzWYMyIiIiGik6L56GAhHYDEaUFnkQPW0wa8eJlp9K3JacPW8wa++ZTM9x5xSbyCxQVIfY+zZsyd2Rqu7SZMmoaamJpkmiYiIiCgL1DR7sGpjLVq9Kka5LLApVvjUMLbVu1Hv9mPp3IqkA4RnNtfivrW7EDxcdsBs7Mro2Njhx31ru+qPjcSgTM8xp/RLav3U5XLh008/7XV7TU0N7Hb7oDtFRERERJlH0wTWbmtCq1fFxGIHnBYTDLIEp8WEicUOtHpVrNveBK1nmsR+UNUIfvOPfQiGI8i3mWBTDDDIMmyKAfk2E4LhCH77z31Q+0j/PlzpOeaUGZIKyL7+9a/jhhtuwN69e2O31dTU4Oabb8a5556bss4RERERUeY40O7H3oOdGOWyxOrQRkmShFEuC2qaO3Gg3T/gttftbMRBTwA2xQhZjn+LKssybIoRzR0BrNvZOKjHAHQFOXWtPuxs7EBdqy+jgxk9x5wyQ1JbFn/xi1/gq1/9KiZNmoQxY8YAAD7//HPMmzcP//u//5vSDhIRERFRZvCqYQTCEdiUxAk2rIoBTR0BePsoqn0kje4gIkLAbEycNMVslOBTBRrdwQG33V22ncXSc8wpMyQVkLlcLmzatAlvvvkmPv74Y1itVhx33HH4ylcGn0aViIiIiDKTXTHCYjTAp4bhtJh63e9Xu8oD2JWBv8UsdZlhkLrOjNkSlBoLhrsSfJS6zMl0HcDQnMVKdWZOPcecMkPSz5wkSViwYAEWLFiQyv4QERERUYYqy7WissiBbfVuOMzGuC10Qgg0uAOYXuZCWe7AU9QvmFSK+5y70djhh8UoxW1b1DQNPjWMUS4rFkwqPUIrfet5Fivad6fFBIfZiD3NnVi3vQkTCh1JB1B6rL7pOeaUGfodkD388MP4zne+A4vFgocffviI115//fWD7hgRERERZRZZllA9rQT1bj/2NHeda7IqBvjVCBrcAeTbFSyYWpJUQKMoBlw9bzzuW7sLrb5QXJZFnxqGxWjAVaeMT7ru1kDOYpXn2wbcvl6rb3qOOWWGftchGz9+PD744AMUFBRg/PjxfTcoSQkzMA53rENGRJT5WHSaMo2eRYT11H0lKBju2jJXVezAgqmpqUP25Lt70egJQhMCsiShNMeMa75SOaiU9zsbO/Dw+j2YUOiAIcHrPqxpqD3kxXVnTMSk0oG9l9M0gSfe2Ytt9e641TegaxVrT3Mnppe58L35lSlZfUv1mFPq6VKHbN++fQn/m4iIKBtk20F+Gv7W72jC6o21qG3xIhTRYDLIqCiwY8ncCpwxuSTd3TuiqmInxp5iw7qdjWh0B1HqMmPBpNKkV6+6G51rRXmBHd5QBGpYg2KUUZ5vx+hBbsnT8yyW3qtvQNeYTzjVwQ+VhqEBz7hQKIRJkybhr3/9KyZPnqxHn4iIiFKKRVUp06zf0YQVa3bCEwihwK7EtqDtbvZgxZqdAJDRQVmiYPKF//t80MFk93Epyflia17Nwc5Bj4ueZ7GGKhOiLEtJB3SUuQa8Jm4ymRAIBPToCxERUcqxqCplmnBYw+qNtfAEQhibZ4XTYoJRluG0mDA2zwpPIISnN9UiHNbS3dWEokHT7mYPnBYjyvKscFqMsWBy/Y6mpNrVe1yiZ7Hy7Qr2NHfCEwghrGnwBELY09w5qLNY3VffEmEmRDqSpDYpX3vttfj5z3+OcJj1DoiIKLOxqCplmi11baht8aLAriQsgFxgV7DvkBdb6trS1MO+6Rk0DcW4VBU7sXRuBaaNdqHdF0LtIS/afSFML3MNaqU8uvrW4A6gZ3qG6OpbVbGDmRApoaTC9Pfffx/r16/HunXrMH36dNjt9rj7X3755ZR0joiIaLBYVJUyTYtXRSiiwdrHeSurYkCrV0WLVx3inh3dQIKmE8YXDKjtoRoXPc5iMRMiDUZSAVlubi7OP//8VPeFiIgo5VhUlTJNgV2BySDDr0bgtPTerORXIzAZuoKbTKNn0DSU46LHWazo6ls0eVBTRwBmowHTy1zMhEhHNKC/Ppqm4b777sPu3buhqipOP/103HnnnbBaufxKRESZiUVVKdPMLM9DRYEdu5s9sCuGXgWQW7wqji1xYmZ5Xhp7mZieQVM2j0sUMyFSMgZ0huynP/0p/vu//xsOhwNlZWV4+OGHce211+rVNyIiokHT8yA/UTKMRhlL5lbAaTFhf5s/bk7ub/Mjx2LC4pMrMrIeWTRoavGq0LT4c2LRoGl8oT2poCmbx6W76OrbpNIclOfb+LuFjqrfhaEBYOLEifjhD3+I7373uwCAt956C4sWLYLf7++1j3ikYWFoIqLMxqKqlGkSpY4fX2jH4pMzuw5ZXyn7W7wqciwm/GjhpEGnvs/GcSHqbiCxwYACMrPZjJqaGpSXl8dus1gsqKmpwZgxY5Lv8TDAgIyIKPNpmuBWIsoo4bCGLXVtaPGqKLArmFmel/ErQID+QZPe48LfBaS3gcQGAzpDFg6HYbFY4m4zmUwIhUID7yUREdEQY1FVyjRGozzgbISZ4IzJJZg/sUi3oEnPcem+Wh4IR2AxGlBZ5ED1tMxfLWcgOTwNKCATQmDJkiUwm82x2wKBAL73ve/Fpb5n2nsiIiKi4S0bg8maZg9WbaxFq1fFKJcFNsUKnxrGtno36t3+QdUi01s2B5J0ZAMKyBYvXtzrtm9961sp6wwRERERpQZXU+JpmsDabU1o9aqoKrKjMxhBm0+FYpBRVWRHzUEv1m1vwoRCR8aNUzYHknR0AwrIVq1apVc/iIiIiChFuJrS24F2P/Ye7ITVJOODz9rR5lMRjmgwGmTk2RSMcplR09yJA+3+jNra3D2QnFjsiJXucFpMcJiN2NPcmbGBJPUPq2ASERERDSPDYTVFj9U9rxrGoc4gWrwqgqEIHBYTTBYjQhGBg54AOg5njfSq4RQ9itSIBpKjXJa4OooAIEkSRrksGRlIUv8xICMiIiIaJobDaopeq3tWkwGHOlV4g2GU5JhjY2M2SlDsCpo6ghCi67pM4lXDCIQjsCmJi9dbFQOaOgIZF0hS/2V+XlUiIiIi6peBrKZkoujq3rZ6N3JtJkwodCDXZsK2ejdWbaxFTbMn6ba7RkNAQl8Vn7ruy7Qw1a4YYTEa4Osj4PKrXXUV7QrXWbIVAzIiIiKiYeKL1ZTEb86tigHBcCQjV1N6ru45LSYYZAlOiwkTix1o9apYt70JmtbvErpxfKEICh1m2C1GtHpVBMMRaEIgGI6g1avCYTGiwGGGLxRJ8SMbnLJcKyqLHGhwB9CzfLAQAg3uAKqKHSjLTbyCRpmPoTQRERHRMNF9NcVhNsITCEONaFAMMpwWY0pXU1J9zkvvs1J2xYhChxmFDgWN7iBafV3bFw2yjOIcC0pzzACkjFtpkmUJ1dNKUO/2Y09z1/hYFQP8agQN7gDy7QoWTC3J2C2odHSZNeOIiIiIKGnR1ZT39rUgHNbQ5g8hrGkwyjLyrCYYjTLmTCgY9GqKHue89D4rFR2bbfVuzBqXi85gJBasOswG1Bz0YnqZKyNXmqqKnVg6tyI25k0dAZiNBkwvc2HB1JGbOXO4YEBGRERENEzIsoRJo5x45aMD8BzOGuiymuBXI/i0xYsciwnHljoHtZqiVxbH7qt7Toup1/2DXd3rvtJUc9CLUS4Lcm1dY1Nz0JvxK01VxU5MONXB2nLDEM+QEREREQ0Tmiaws8GDUTkWTCi0QxOA2x+CJoAJhXaU5liwq9GT9DksPc95DcVZqehK07TRLrT7Qqg95EW7L4TpZa6sKAcgyxLK822YVJqD8nwbg7FhgitkRERERMNE9BzWxBJHwjNkncHwoM5h6XnOa6jOSnGliTINAzIiIiKiYaL7OSxJkpBjjd/6N9hzWHqf8xqqs1LRlSaiTMCAjIiIiGiY0Psclt7tA1zBopGHZ8iIiIiIhgm9z2GxJhZR6nGFjIiIiGiY0PscVvf2dzd1wmkxwiBLiGgCnkAYBY7Bn/PSI6U+USZjQEZEREQ0jOh9Dquq2InTJxVj9cZabK93IxTRYDLIqCiw48IvjxlU+3ql1CfKZAzIiIiISFfhsIYtdW1o8aoosCuYWZ4HozF1pyY0TWTteSO9+l5V7ETFV+y6jHtNswcbdjbDYgRG51oQDEVgNhlgMQIbdjZjXIEtqaCpe0r9CQU2fNriRWcwDIfZiAkFdnza4sO67U2YUOgY9BjpPSeJBoIBGREREelm/Y4mrN5Yi9oWb9xKypK5FThjcsmg28/m7W169j1R2+/vaxt029Gg6d/723CgzQevGoEQgCQBdsWAsrwgynKtSQVN0ZT67T4Vv685BK8a7ta2EVNG5wwqZX+U3nOSaKAYkBEREZEu1u9owoo1O+EJhFBgV2JnmXY3e7BizU4AGNQb4Gze3qZn3/Vs+0C7H+s+aURNcycimoDJIMEgSYgIgc5gBDXNnVi7vRHnHD96wEGTVw1jV1MH9jR1a/vw+bTOYBgfftaGiSXhpFPqA/rPSaJkcG2WiIiIUi4c1rB6Yy08gRDG5lnhtJhglGU4LSaMzbPCEwjh6U21CIe1pNrvvr1tYrEDTosJBlmC02LCxGIHWr0q1m1vgqaJozc2xPTsu97j0uYPYneTBxFNwGKUYTLIkGUJJoMMi1FGRBPY0+RBmz844LYVWcK+Q16ENQGL6XDb0uG2TTLCmkDtoU4oSW5X1HtOEiWLARkRERGl3Ja6NtS2eFFgVyDL8W83ZFlGgV3BvkNebKlrS6r96Pa2US4LJCn+DbokSRjlssS2t2UaPfuu97j8+7M2qGENRlnqtSVRliUYZQnBsIZ/fzbw53VbQwdCYQ0GCQn7bpAANaxhW0NHUn3Xe04SJYsBGREREaVci1dFKKLBqhgS3m9VDAhFNLR41aTa96phBMIR2PooQGxVDAiGI4Pa3qaX7n0XQqDDH8KhziA6/CEIIQbVd73HJRjuWlkTQqDnGps4fHv36waiuSPYFXjJEkJhDWpEQyhy+P/DGgyyBEmS0Nwx8NU3QP85SZQsniEjIiKilCuwKzAZZPjVCJyW3p//+tUITIauVYlk2BUjLEYDfGoYTospYftmowH2PgKTdIr2vb7dhwZ3EG0+FeGIBqNBRp5NwSiXOem+6z0uo3MtMBlkaEJDOCIOB0mAEEBEE4AEmGQZo3MtA2671GWGUZYACAQiAt13VcoSYDFKkCUJpS5zUn3Xe04SJYsrZERERJRyM8vzUFFgR4tXhabFn8nRtK5ViPGFdswsz0uq/bJcKyqLHGhwB2KrMlFCCDS4A6gqdqAs15r0Y9BLWa4VuVYT3q9tQ7MnAIvJgDy7AovJgGZPAO/XtiHPZkqq73qPy4JJpSjJsUBAglEGNCEQjghoQsAoAwISSl0WLJhUmlTbdrMBvpCAEIBB+uJLCMAXEnCYDUm1Deg/J4mSxYCMiIiIUs5olLFkbgWcFhP2t/nhCYQQ1jR4AiHsb/Mjx2LC4pMrkq79JMsSqqeVIN+uYE9zZ1z7e5o7kW9XsGBqyaDrVWmaQF2rDzsbO1DX6ktdkpBot4QAYpv/xOHv0Ws7YH/pPS6KYsDV88bDajIgFBFQDDLsZgMUg4xQRMBmMuCqU8ZD6WNb4NH6nmM1oWuN7PBth7sp0DVkTqsp6b7rPSeJkpV56/hERERZKpsLFOshmj78qX98it3NnbGaT8eWOLD0lAmDTi9eVezE0rkVsXpbTR0BmI0GTC9zYcFUfWp5paJO2IF2P9p9IcyuyEOjO4hWnwpvMAyDLKPEZUVpjhntvlDS9bai4/LG1kZsPeCGLxSGzWTEcWNcqJ5WOuhx+facCgDAk+/uRaMnCE0VXVsJc8y45iuVsfsHaktdG9SwQEmOGW1eFWq3bYtmo4Q8mwI1LLClrg0njC9I6mdE51y0DlmrVz08J51YfDLrkFF6MCAjIiJKgWwuUKw3Seo6Z9T138AXy0ODV1XsxIRTHSkPhPWs5RVNvDGh0IExeTZ4AmGoEQ2KQYbTYkRECNQe8g4+IYmEL4ZaSn7VLZHRuVaUF9jgDUWghjUoRhnl+TaMHsQW0WjSjbI8K8rzrGjzhRCMaDAbZOTZTNAAHGjzDzrpxhmTSzB/YhG21LWhxauiwK5gZnkeV8YobRiQERERDVI2FyjWU/civIUOc6wI756DnSktwivLUlIrSX3pWcsrmoLdaTHBYTZiT3Mn1m1vwoRCR1KBX8/EGznW+OQb/mB4UIk3us/HslwrbIoRPjWM7fUdaHAHBj0fuz+vJTmW2PNac9A7qOc1PumGCQWO+OQd3kAoZUk3jEY56VU2olTjRwFERESDkM0FivWUzUV49a7lpWfiDb3no57PK5Nu0EjFgIyIiGgQsrlAsZ6yuQiv3rW89Ey8ofd81PN5ZdINGqm4ZZGIiGgQvnjznng1w6oY0NQRyMgCxXrqTxHeVq+akUV4h6LGmV4JSfSej92fVyEE1LCGiBAwSBIUozzo55VJN2gkYkBGREQ0CNlcoFhP2VyEN7qlcFu9Gw6zMW6lKbqlcHqZa9A1zvRISKL3fIw+r+0+FcGQgD8UgSa6sixaTQaYTdKgn1cm3aCRZmT9dSAiIkqxoXrznm2i54F2N3tgVwxx29ui54GOLXFm5Hmg6JbCercfe5q7tv9FE1c0uAMpq3EW/VmpTEii93ycWZ6HYqcZnzR0wGyUYTYZYJBkRIRAZzCEFq+GqaNzBv28MukGjST8qIGIiGgQhqpAcbbJ9vNA0S2F00a70O4LofaQF+2+EKaXuTI6a6be81GWJYwrsEGWJIQiAhFNQIiu/w9FulbKxubbRtx8JxoMSfRM70NJ6ejogMvlgtvtRk5OTrq7Q0REQ6x7HbJguGtbWFWxIyUFirPZ+h1NsfNA0cLQ4wvtWXMeKFuLfes1H+tafXjwzd3oCKjY3diJdn8IEU3AIEvItZlwTIkDORYFN551TEpX/oiyzUBiA25ZJKKsla1vlGh40qtAcVS2zvczJpdgXmUh1u1sRKM7iFKXGQsmlULpI9lHpkn1lsKe9Hpeq4qdqPiKPeXnsKJJQyaVujCpxIm9B73wqGE4FSMqi+wQkpSaotZEIwgDMiLKSt0//Q2EI7AYDagscqB62shejaD00uvNezbP90R9/+yQPyv6rjc9n9dEbb+/r23QbUeThtS3+9DgDqLNpyIc0XDIIKPdH8Yol3lEJrEZKtn6wQwdGV8tRJR1apo9WLWxFq1eFaNcFtgUK3xqGNvq3ah3+zP6fAfRQGXzfM/mvutNz7HRs+2yXCtyrSa8uaMJirGrILTJYkQoItDsCeDzNh8WTCkZcUlshkI2fzBDR5aZJ2mJiPqgaQJrtzWh1atiYrEDTosJBlmC02LCxGIHWr0q1m1vgqbxeCxlv2ye79ncd73pOTZDMu7RBRkhAETbEYe//+IWSp1okL2t3o1cmwkTCh3ItZmwrd6NVRtrUdPsSXcXaRAYkBFRVjnQ7sfeg11pqLuncwYASZIwymVBTXMnDrT709RDotTJ5vmezX3Xm55jo/e4H2j3o90XwuyKPJTkWBEIaWj3qQiENJS4rJhdkYd2X2hEPq964Ycbwx+3LBJRVokeKLcpibfDWBUDmjoCPFBOw8JQzvdUn00ZLq9VPc7s6Dk2eo97tP0JhQ6U5drQ0OGHX43AqhgwKscKDYJJPVJsIEE2M1tmJwZkRJRVogfKfWoYToup1/1+NcID5TRsDNV81+NsynB4rep1ZkfPsdF73Lsn9Wh0B9HqUxHWNBhlGfVtAZQyqUfKDZcPN6hv3LJIRFmlLNeKyiIHGtwB9CyjKIRAgzuAqmIHD5TTsDAU812vsynZ/lrV88yOnmOj97iX5VqRazPh/do2NHX4YTHJyLMpsJhkNHX48X5tG3Jtpox9XrNR9yA7kWz4cIOOjAEZEWUVWZZQPa0E+XYFe5o74QmEENY0eAIh7GnuRL5dwYKpJUwDTMOC3vNdz7Mp2fxa1fvMjp5jMyTjHn3YPbbPRb/PvGc0u2X7hxt0dAyliSjrVBU7sXRuRWwrUVNHAGajAdPLXFgwlel/aXjRc77rfTZlqF6rqT7nNRRndqJj88bWRmw94IYvFIbNZMRxY1yonlY6qLGJtb3tcNtqBDbFgOPKcge93fJAux/t/q6kHtE6ZJ3BMIyyjJIcC0pzzGg7nNSD55lSIxpk17v92NPcNS+tigF+NYIGdyCjP9yg/mFARkRZqarYiQmnOlggkwYkW4uq6jXfh+Jsit6vVT3OeQ3pmR0JXywpSalNGS+EgF+NwBsMQQKgCW3QbcYn9bCiwR2ALxSBzWTAKJcFGsCkHjrgB5HDGwMyIspasizxE1jqt2wvqqrHfB+qxBt6vVb1KoA8FOPSve9luVbYFCN8ahjb6zvQ4A4MujD0Q2/twa5GD9RwBJoQaOlU0eAOYFdTJ244c+Kgk7UkTOrRzqQeeuIHkcMXz5AREdGwx6KqiWXz2RQ9z3npPS56F4Z+7l/78UFtKw55AugIhNEZDKMjEMYhTwAf1LbiuX/tT/r8G5N6pFf0w41JpTkoz7cxGBsmGJAREdGwxqKqfcvmxBt6FkDWe1z07PvnbT68u/sgOoNdWwYVowyryQjF2PWWrzMYxru7D+LzNl9SfQfApB5EKcaAjIiIhjU93/wOB9GzKdNGu9DuC6H2kBftvhCml7kGtW1Ob1+c80q8Nc6qGBAMR5I+yxQdl6mjcnCgzY//fN6OA21+TBudM+hx6d53IQQ6/CEc6gyiwx+CEGJQfd97sBPNHQHIACwmAyAEwpoGCAGLyQAZwMGOAPYe7Eyq792TehQ7LQiENLT5VARCGkpyLJhdkRdL6kFE/cMNvkRENKyxqOrRZePZlCErPK1D0o3u57Aa3AE0dwQRimgwGWQU55gxymVJuu+HOlWENQHFKMMbDCOkCQjRtXhlkiVIsgQ1rOFQp5pU37sn9RiTZ4MnEIYa0aAYZDgtRkSEYFIPogFiQEZERMPakL1xz3LZliQnes5rW70bDrMxbvUzes5repkr6bNMeibdKMu1Itdqwt+2N0INRdC1W1YAkNDmU7GvxYdF00qT6nuBQ4EEwKdGYJAAgyxBOhxIqhENkTCgyBIKHEpSfe/5esqxxr+m/MEwX09EA8Qti0RENKxlc+IK6pue57yG4txhm1+FJxBCIBSB0SDBqhhgNEgIhCLwBEJo84WSand8oR1mkwGHdykCkA6f7ZIgBKBpgNlkwPhCe1Lt8/VElHoMyIiIaFjL5sQVdGR6nX/T+9zh520+7Gr0wGUxId+uQAggENIgBJBvV+CyGLGrsSOpxBsGSUK+TYFilCBJEiKaQDgiENEEJEmCYpSQb1dg6JmQo5/4eiJKPa4nExHRsBd94/7GtkZsPeCGT43AphhwXFluSuuQZWvh6WxWVexExVfs2FLXhhavigK7gpnleTAak//Mufu5w0hEw95DnegMhuEwG1FZ6Bj0ucNPD3nh9oVQ6FRgNsjoDEZitbwcZgOCEQ0tnSo+PeTF2IKBrWT5QhGU5VkhScBBTwDBiAahAZIMmA0yCp0WjM61wheKJNV3oNvraevh11MoDJvJiOPGuFA9rTQlrye9X0t8rVImYUBGREQjh+j6El3/02vL1WBke+HpbJVo3N/f1zaocY+ek/rws1Z8Ut8BrxqOJcbYpLRgyugcjHJZB3VOSkhAMKShtVOFP6RBEwKyJMETkGEzJ9+uXTGi0GGG2x9CXauGYOTwHI8AQtPgMHfdn5IzXjokPAH0fy3xtUqZhgEZERENe3EJGvK6JWho6EBDx+ASNPRsf5TLAptihU8NY1u9G/Vuf0anj89meo17Wa4V7oCK92vbIISAySDBIHdt/+sMhvF+bRtOPdaY9Dmp8YV2WI0GHGgPwGSQYDbKkCUJmgC8agTt/jBKnOakznmV5VrREVCxvb4DQgiYDYeTegggrAlsr+9AkVMZ1BkvPROe6P1a4muVMhHPkBER0bCmd4IGFp5ODz3HPRzWsKO+A5oQMMgSDLIMSer6f4MsQRMCO+rdCIe1pPpe5rIi12ZCRNMghDi8siR1LeAKgYimIc9uQplr4EFTOKzhk2jfpa4zX7IkQZYlGCQc7ntH0n3Xc9z5WqWRigEZERENa3onaGDh6fTQc9zX7WxEuy8Ep9kAs1GGJroSY2hCwGw0wKkY0OYLYd3OxqT63tARQJ5dQUmOBfLhumD+UARqWIMsSyjJsSDXpqChI5B0322KDEgSAiEN/pCGQEgDJAk2RR5U3/Ucd75WaaTilkUiIhrW9C4MzcLTR6dHAgU9x73RHURECOQoRsiSjIgmICAgQTq8QqYh4Auh0R1Muu+KUcbJlQXYd8jbVRha02CSZZTkmFFRaIfbH0q672FNQEQEwlr8ua5QRECIrmyLg+m7XuPO1yqNVAzIiIhoWNO7MDQLTx+ZXgkU9Bz3UpcZBklCMCxgUwCjoXv2CiAYEjBIEkpd5kH13WIyYHZFPjyBMNSIBsUgw2kxojMYRiCkJdX3khwzIppANJdHtOeH89kgpAEGSaAkZ3B912Pc+VqlkYpbFomIaFjTu5AtC+X2LZpAYVu9G7k2EyYUOpBrM2FbvRurNtaiptmTdNt6jvuCSaUoclrgU8PQtPizVpqmwaeGUZxjwYJJpYPuOwDkWE0odJiRY+0KEgbT92NLHeg+HIdrQqP7Dj0huq4bbN9TPe58rdJIxYCMiIiGNb0L2bJQbmJ6J1DQc9wVxYCr542H2WhAqzeEzkAYgVAEnYEwWr0hWIwGXHXKeCiKIeP6/nFdB7r/M0188fXFz++6LtP6ztcqjVSSSGURlhGso6MDLpcLbrcbOTk56e4OERH10H3rXDDctTWpqtiBBVNTX9tIj/azTV2rDw++uRu5NlPC7WGeQAjtvhBuPOsYlOfbkv45eo77/et24XebPkNnMARNALIEOC0mfHvOONy84NhBta1X35/ZXIufvr4DRhnwqRq6r+/JAKyKjIgG/HjRZHx7TsWg+r7mPw14v7YNnWoIDsWEE8bn4avTRw163PlapeFgILEBN8kSEdGA6JGgYSjaryp2YuwpNqzb2YhGdxClLjMWTCpNepVjqNtX1YhubQNd6dK31LWhxauiwK5gZnkejMbkN9J0T6CgqmFs3tcCtz8Ml9WIOeMLUpZAQa9xr2n2oNWr4kvlTmzZ746df5sxxolWr4qaZs+g37xXFTsx+iQLfr1pLz5vDWBMvgVLThwHm613ANtfE0scUIwywhENZiMQDHedHZMAmI1d2xUVo4yJJcltWYz6rMWHf9W2Yu/BTqhhDYpRhgaByaNdKRmXMSdb8cKW/TjQFkBZngUXzxwLiyU1b1urip2YcKpD199jRAOR1oBsxYoVePnll7Fz505YrVacfPLJ+PnPf45jj/3iU6dAIICbb74Zzz//PILBIKqrq/H444+jpKQkds3+/fuxbNkyvP3223A4HFi8eDFWrFgBo/GLh/fOO+/gpptuwvbt21FeXo7bbrsNS5YsievPY489hvvuuw+NjY04/vjj8cgjj+CEE07QfRyIiLKFXgkahqL99TuasGrjvrg3kM//Xx2Wzh2PMyaXHL2BfrS/emMtalu8CEU0mAwyXvi/z7FkbsWg239mcy1+8499OOgJICK6Ekrc59yNq+eNH9Qqx5H6XlFgH1TfowkUXt9aj9pDvrhsfx9/3oFxBTbMHJs36AQKeox7dLvlK//+HD71izUmNRLBO3taYVPaUZZrxYRCx6DexCdagVv1z/244uTkV+C+PDYfY/Ks2NHgiRtzAcAfBiRomFJkx5fH5ifd7/U7mrBizU54AiEU2BVYFQP8agR7mjuxYs1OABjUnE8035/652cpm+9A1/bFwazMEqVSWs+Qvfvuu7j22mvx3nvv4c0330QoFMKCBQvg9Xpj19x444147bXX8NJLL+Hdd99FfX09zjvvvNj9kUgEixYtgqqq2LRpE55++mmsXr0at99+e+yaffv2YdGiRTjttNPw0Ucf4YYbbsDVV1+NtWvXxq554YUXcNNNN+GOO+7Ali1bcPzxx6O6uhrNzc1DMxhERBlOzwQNere/fkcT7nrtE3xU1w5fMIKIpsEXjOCjunbc9donWL+jaVB9j75B3d3sgdNiRFmeFU6LEbubPVixZueg2n9mcy3uW7sLjR1+mE0G5NlMMJsMaOzw4761u/DM5tqM7HtZrhXb693Y1yMYA7qCg9oWH7bXuweVQEGvvh9o9+OJd2vigrHufKqGx9+pGVS9qvvX7cLKd/eiIxiCUZZgNUkwyhI6giGsfHcv7l+3K6l2ZVmCySD3GvMoAcAoy0kHkuGwhtUba+EJhDA2zwqnxQSjLMNpMWFsnhWeQAhPb6pNuvC03vOdKBOlNSB74403sGTJEkydOhXHH388Vq9ejf379+PDDz8EALjdbvz2t7/FAw88gNNPPx2zZs3CqlWrsGnTJrz33nsAgHXr1uGTTz7B73//e8yYMQMLFy7EPffcg8ceewyqqgIAVq5cifHjx+P+++/H5MmTsXz5clxwwQV48MEHY3154IEHcM0112Dp0qWYMmUKVq5cCZvNhqeeemroB4aIKMPonaBBz/bDYQ2Pv12Dg54AjBJgUQywKSZYFAOMEnDQE8Dj79Qk/QZSzzeoqhrBb/6xD8FwBPk2E2yKAQZZhk0xIN9mQjAcwW//uQ+qGsm4vvv8Iexp6jziNXuaO+HzhzKu75+3dKIzeOQx7QxG8HnLkR9fXwKBMH636TOENQGbUYJilGGQZShGGTajhLAm8MzmzxAIDHw7Z+2hTuxp9qCvcEtC14cftYeS6/uWujbUtnhRYFcgy/FvI2VZRoFdwb5DXmypaxtw23rPd6JMlVFZFt1uNwAgP79rGf3DDz9EKBTCmWeeGbtm0qRJGDt2LDZv3gwA2Lx5M6ZPnx63hbG6uhodHR3Yvn177JrubUSvibahqio+/PDDuGtkWcaZZ54Zu6anYDCIjo6OuC8iouHqQLsfew92YpTLAkmKf6snSRJGuSyoae5MesVAz/Y/3N+KPc2dMMoSbGYTjLIESULc9zVNnfhwf2tSfdfzDeq6nY046AnAphgTtm1TjGjuCGDdzsaM6/v9G3bhaKGQJrquS0b3vkuShGAoAp8aRjAUgSRJg+r7z9fuTOl1Pb2wZT86gyEospRw3BVZgicQwgtb9g+47bd2NCNweGXPIPX+AgC/quGtHcntAGrxqghFNFj7OKNnVQwIRTS0eNUBt633fCfKVBkTkGmahhtuuAFz587FtGnTAACNjY1QFAW5ublx15aUlKCxsTF2TfdgLHp/9L4jXdPR0QG/349Dhw4hEokkvCbaRk8rVqyAy+WKfZWXlyf3wImIssAXCRoSn/exKgYEw5GkEzTo2f7upq4zYxaTjB6xHiQJsJhkBMMadh9lNacver5BbXQHERECZmPi9Q6zUUJECDS6gwNuG9C375+3BlJ6XU/RvgNAfXsAdW1+fN7mR12bH/XtXW0m2/cWb/9W7fp7XU8H2gLQBGDo412YQe4KVg+0DXxs3AE1FgjLsgRDt6/oNkXt8HXJKLArMBlk+PtYpfKrEZgMXcH8QOk934kyVcYEZNdeey22bduG559/Pt1d6Zdbb70Vbrc79lVXV5fuLhER6SaaoMHXR0DkV7tSRyeboEHP9i0mAyQJECLxmzxNSIcDs+Sy8un5BrXUZYZBkhAMJ96qGQx3JTwodZkH3Dagb9/H5FtSel1P0T7VH86UZzRIsJoMMBokeNUw6g+vpibT99G5/etTf6/rqSzPAlkCIn0sIUa0rgQfZXkDb7/QYf5iu2LPykaHv5cOX5eMmeV5qCiwo8WrJiya3eJVMb7QjpnleQNuW+/5TpSpMiIgW758Of7617/i7bffxpgxY2K3l5aWQlVVtLe3x13f1NSE0tLS2DVNTU297o/ed6RrcnJyYLVaUVhYCIPBkPCaaBs9mc1m5OTkxH0REQ1XZblWVBY50OAOoGf5SiEEGtwBVBU7kk7QoGf7X67Ig8NsgleN9DqDpmkCPjUCp8WEL1cM/A0koO8b1AWTSlHktMCnhhO27VPDKM6xYMGkxH+r0tn3G087ps9zTFHS4euSMaMsF2ajAf5QBBajFLcV1WKUum43GTCjLHfAbT92yZdSel1PF88cC4fZBFUTCcdd1QScFhMunjl2wG3PGpcH5XC5gojW9fqJfkUDQMUoY9a45Oa70ShjydwKOC0m7G/zxxVX3t/mR47FhMUnVyRVMkHv+U6UqdIakAkhsHz5crzyyivYsGEDxo8fH3f/rFmzYDKZsH79+thtu3btwv79+zFnzhwAwJw5c7B169a4bIhvvvkmcnJyMGXKlNg13duIXhNtQ1EUzJo1K+4aTdOwfv362DVERCOZLEuonlaCfLuCPc2dcW/C9jR3It+uYMHUkqQzt+nZ/rh8O+ZVFUCWgI5AGMGwBk0TCIY1dATCkCVgXlUBxuXbk+q7nm9QFcWAq+eNh9loQKsvBJ96OEOkGkGrLwSL0YCrThmfdM0tPfvuViMY7TryCs9olwXuJBM0NHUGMTrXAovJgI5ApMfzGoHFZMQolwVNnQPf3lbosqGq6Mgp0auKbCh0JZc23WIx4oqTx8EoS/CFBdSwhoim4f+z9+fhdZ3lvTf+WeNee9ZkSZY8D4kzGIIJpE7C1KQOOdBDW8qBtgfCkHKVhhbanhZoSwfaHk6bl/e0PT2FXwtlKnAovXpogTckEAqExA0ZCImTeEqs2JYsyZb2vPfaa3p+f6y9tyVbjq21tSzJeT7XpSjSXn706FnPXlr3uu/7+3W8gLonMFSFt+7eGMl3qzeVYMdwFl1VEIAXhIGZF4QKi5qqsGM4S28qepbppiuG+NCtO7hsMEvF9hgvNKjYHpcPZfngrTsiS97Hvd8lkpXKsvqQ3XHHHXzxi1/kX//1X8lms51+rXw+TzKZJJ/P8653vYvf/M3fpK+vj1wux6/92q+xe/dufuInfgKAPXv2cOWVV/LWt76Vv/iLv2BycpLf//3f54477iCRCC82v/Irv8Lf/M3f8Du/8zu8853v5Dvf+Q7/9E//xDe+8Y3OXH7zN3+T2267jWuvvZaXv/zl/OVf/iW1Wo13vOMdF39hJBKJZAWybTDLO27Y1PEJmyrbJHSNnaN59lzVvU9Ye/y7Hj/BQ2MFqo5LxjR4+eZeXrtzbeTxVVXhV39yGzN1h33jJeqOhxBh/1jS0Lh6NM97XrOtKz+p9g1o2w9rtuZgaCqXD2W57frufMjavkuf/P6zTJZtKna7bMvi9lds6dqXqT23tkfbdFlg6AqXDWa78vKqOR4v3tBDcrLMMyfnS98rwNY1KS4fznXVd9ibNrlx2xoeP16gUHOptTyr+tImO9flUVrHReHbv/Uabv7Yv3P4ZP2s17atSfHt33pNpHHbtH3GPvfAGJWmh+OHezJnGbxtd3QfstGeJHuuHMYNAo7P1Kg2g44xdCahsq4/zS1XDXdlNwDhvnnV9jVLaiYOc/Z7y4es7oTndG0+ybtuXDofMolkJbGsAdnHP/5xAF796lfP+/6nP/3pjmnz//yf/xNVVXnjG984zxi6jaZpfP3rX+c973kPu3fvJp1Oc9ttt/GRj3ykc8zmzZv5xje+wW/8xm/wV3/1V6xbt45PfvKT3HLLLZ1j3vzmN3Py5En+4A/+gMnJSa655hq++c1vniX0IZFIJC9ktg1m2fLqDOOtvp20qTPak+wqmJnLczN1HhybnWfeHCC4YiTfVcC3bTDL23Zv4h/ue5aD01UcP8DUVC4byvC23ZuWxNQ6rhtUgJGeJKO9FhXH66zLaI/FSJc31W029qe4blMfKgoVxyVrGrxsUy8b+6Mb57b7Al952SA/tUNh75EZSg2PfFJn9+Z+moGgWHe77jsEwUg+CSid8zqSt7B0FVC6Mp6+7frN/P/+/RDjZacT1IzmTG67fvP5/ukF8YZrRtARfOfASUq2S94y+MnL1/C6a0Yij9nONv9wbIYThQa6HnQeQGiqyppMoqts9lx0XeXlm/u7HudM3rp7E2988Sh/98AzHJ+1Wddn8e7rt5JKGUv+sySSlYAizizWl0SiXC6Tz+cplUqyn0wikUgi0Db5rdgu/WmTpKnRcHxmag5Zy+BDXZRCtU2nZ6oOOUtHVRWCQFC2PfozJu+4YWmCsjiIc13g9NrM1hzW5i1Spk7d8ThRsulLR1+bIBB8/LvPsG+ixPbBzDw7AyEEh6ar7BzN8yuv2hopOAgCwZ9+/Sm+9fQUph76jxmagusLKraL4wXsuXKI33vdlZHGbxsUN1vqnwk9FJuoOx4JXeO3b7m8q2xNXOsOp43QZ2tNNEVBUQRChAqFfekEf/jTV3a1Z+Lm3qenOtlm1w8wNJVN/emuMrYSycVmMbHBihD1kEgkEskLmzhNfueaTl82lGFtT5KhnMXaniSXDXVvah0nca4LxGvIHXffIUBHNUQI6BRFio6aYNQzGrdBcdxG6J+5f4ym57NjKMNIT5I12TCbumMoQ9Pzu9ozcdN+AHFwukLW0hntTZK1dA5OV/joXfu59+mp8w8ikawyZEAmkUgkkmUnToPiuE2t4yTOdYH416bdF3j1SJ5i3WXsVI1i3WXnaL7rrOR4sUGx7vKyTb0M5ZLYbkCx7mC7AUP5JC/b1Eux7kaae9wGxXPXHaDccDlVbVJuhL5m3ax7e89kTI3JcpPpSpNTVYfpSpPJcpOMqXW1Z+Ik7gcQEslKZVl7yCQSiUQigfkGxUK0VOdaAg2mrpI0NWZrTiST39Om0wv3WyVNjamyHVn8IU4uxLg56rrAxVmbuPoO23PfMpBhXW+Kiu11esiylo4vBGOnapHmfiEGxXUnukFxe+62q/H0iQKFuoPnB+iaSm/KZNNAKrIR+kzNoeF4NBQFPxAkdBVVUQgE1Bwf2wtAiMh7Zi5BIJb0vC7mAUQcvWsSyXIhAzKJRCKRLDttg+Ji3aHpChquTyAEqhKa/SYMJbJB8VzT6ax1tihAt6bWcTLXuDlrnV3U0o1xM1y8tVFVhfV90QVCFuLMueeS8+ffaHqR5z7XoDi1wNJ2a1CcNnUcL+CR52Zx/QAVBaEIPC9gqtxgttZkfV8q0tx7UwauLwhEQCahEQiBJ8LqTktXqDZ9VEWht0uBjMPTlY7iqu35WLrG1jUZbrk6uuJq3A8gJJKViixZlEgkEsmys2t9L4PZBBNFm2rTRdfCQEzXFKpNl4mizVAuEcmgOG5T6ziJ07gZVvfaxDn3uA2K1+Ysmm7AZLnJqUqTo4U6R2caHC3UOdUqLXS8gLW55/dxW4jhrIWpqzh+QLXpU7Y9yg2Psu1Rbfo4fkDCUBnOLn7sNm1Bkn0TJXpSBlsGMvSkDPZNlPj0/WMcnq5EGnfuA4iF6PYBhESyUpEBmUQikUiWHVVV2NifQlVClTw/EAgRfnb9MFO2oS8VqRzqoohLxEScxs2wutcmzrnHbVB8omxTtl0ajkfN8VEVMHUFVQnLChuOR6nhcqJsL3ps2w8YzCUQAuqOjxACTQ2D1PBrWJO1sP2VJwQT9wMIiWSlIgMyiUQikSw7oXiBwu6tffSnTRwvoGyHnlv9GZPdW/sAZUWKS8TNTVcM8aFbd3DZYJaK7TFeaFCxPS4fyvLBLiXvYXWvTZxzf+vuTfz2LZcznEvSdH0KdZem67M2n+S/dSl5X2o4HC800FSFpKGiKAp+EAqpJA0VTVUYLzQoNRZfmpc0NIRQ6EmZpEyNQIDjCQIBKVOjJ2UiRHhcFOIUgon7AYREslJZeQXzEolEIlnRLHUjP5wWOdgxnOfywSz7TpSp2B5ZS+fqtTlQlcgCDW3iNrWOkzhNpyFcmw03prhn/ySTpSbD+QR7dgxHzgCdiecFsc593fVJvvzoUcYLNqO9Fm/etQHL6v4W5627N/GGnWv5yF1PdQyK/+DWK8llovWOtRmbqdFwPCxDI2morYApzASbukLDDcsix2ZqXD3as6ixw90sSBkq6/Jpxks2thdg6SqjeYuZuouCIOqunysEI4Q4S0ylWyGY9gOGT//gCM+crDJdDn3ILhvM8PYbNksfMskliQzIJBKJRHLBxNHID6cFGg5MljkwWaHYcPEDgaYqHDlZ4/LhLFnLWJHiEhcLXVdjU5a79+kpPn1/eAPseAGmrvJ/fniMdyzBDXDcJr+f3zvGJ+87wsmK3VHm/IcfPMftr9jcVRYL4GP3HOBzDzxHtekSCHhoDL715Enedv1GfmvP5ZHHVRQFVVXwvICKH+AFAiFAUaDpKSDCvXpmBupCqLs+A5kET5VtnpttdLzYSsB0xaE/bbCxP03djeah1n6vThTrTJaazNYdvCBAV1X6UibD+UTXQjAb+1Nct6UPVQ17SDMJg5dt6mVj/+p870ok50MGZBKJRCK5INqN/LM1h7V5i5SZpO547JsoMVFqdFUiNtqTRCB44NkZRCBIJXQMLewnO1VtMvOswy1XDq9IcYnVzr1PT/HHX3uK2VoTTVFQFEG9KXjsWJE//tpTAJEDp7bJb8V26U+bJE2NhuN3TH67GRvCYOzOuw/Q9HxSpk5CD5URJ8sN7rz7AEDkoOxj9xzgE997Bi8QmKqCpoIfQLnp8onvPQMQOShbk0lgGRrlhoMQCpqqoCihn7XtBigK5JIGayJk4tKmzlTZZqbmnmWMLYCZmstU2Y4cMI32JOlJGXzrqSlMTSGbNDA0HdcPFSKPFer81JVDkd+rc68z2wYzpEyduuPx1IkKk+Xmii+jlUiiIItwJRKJRHJe4mzkb49/dKZOEAhMXQtvUAFNVTB1LXx9thZ5fMnCeF7A3/77YU5WbHQFLFMjZRpYpoauwMmKzd9+93AkI964TX4dx+eT9x2h6fn0pQxSpoamqqRMjb6UQdPz+dQPjuCcQ7Hv+bBtj8898BxeIEjpoReepqqYukpKV/ACwef3PodtRyvLu2a0h7SpI4QCCBw/oOkGOH4AhNmyTELnmkWWKwL0WwZjp+oIQFfAUBV0tfU5TL4xNlOnfwGbgwum/TY8M4PX+jpqOWTc1xmJZKUiAzKJRCKRnJc4G/khNISdrjQZyVtkEhqeL7DdAM8XZBI6I3mLqXKTR48VluLXkbR45Ogsh6ar6KpCKmGAAC8IQEAqYaCrCoenqjxydHbRYy/G5DcK9+yf5GTFJmXqC46fMnWmyzb37J9c9NhffvQo1aaLqSoLjm2qChXb5cuPHo0096lqk56UgaJAIMJgydQVDDU0cFYUyCcNpqqLN57+ymPHWt5mc+OmdmdZeOPnegFfeexYpLmPFxsUGy4v29TLYNbCdgMKdQfbDRjKWbxsUy+FuhvpWhD3dUYiWanIkkWJRCKRnJe5jfwL0W0jf9sQdjCXRFMUHC/o9AOZuoovBOOFhjSEXWIOToU9YylTpWJ7eEHQ6WXSVRVdU2g4AQenqly3ZWBRY8dt8jtZauILQUJfOB+T0BXqjmCytPigZrxgEwjQzvHYWlPB8cPjolCxXRqOT1/aoN70sb2AIAjXPW1qpBIatutTsd1IcxeEv38gIBAC0RpbU0Np/aYnIs+9fS3YMpBhXW/qLFEPX4jIAjxxX2ckkpWKDMgkEolEcl7ajfx1xyO7QKlTw/G7auSfawibtQwSZ0hyN5qeNISNAcvQEAhqTR9FafUyqWEvk+sHOJ4AJTxuscw/p2dHNt2a/A7nE2hK2DOWWmCIphcG9MP5xfdhjfZaqErYM7ZQUOYHoCrhcVGoNj0ark9fOsH6Xo1q0+8IY2QSGjXHp2J7VJuLDzzacxcCTF1FCBAIFMI+NdcLupr7mdeCXHL+9aDR9CJfC+K+zkgkKxVZsiiRSCSS8zLak2TrmgwnSjZCzO/fEEJwomSzbTATuZFfGsIuD7s29qCpKm4g0JQwyFAIP2sKuIFAV1V2bexZ/Ngxn9M9O4ZZk7WoO96C49cdj8GcxZ4dw4se+827NpBJGDiBWHBsJxBkLYM379oQae6Zljx80w1QFIVc0qAvnSCXNFAUhaYbkDI1MhGk++fOXQRB61yGmTGxBHOP81oQ93VGIlmpyIBMIpFIJOdFVRVuuXqIvrTJoenqPMPWQ9NV+tIme64aiuzpJQ1hlwdDVelPGaiKghMIvCD0w/ICgROEvlj9KQNDXfy6x31OTVPj9ldsJqFrzNZd6o6PHwTUHZ/Zuoula7zrxs2RvNQsS+dt129EVxXqnghLaIMAxwuoewJDVXjr7o2Rvc6yCYMNfSl0TWG25tD0fAIhaHo+szUHXVdZ35cim1i88Ebcc4/zWhD3dUYiWanInK9EIlm1xGFQLDk32wazvOOGTR0fsqmyTULX2DmaZ89V3fmQwXxD2INTlU5fyuXD2SUzhJV7Zj5112fzmgyKAtOVJq5/OhukqwqDuQSbBjKRPava5+wf7nuWg9PVjg/Z5UMZ3nHjlq7PaVvS/pPff5apSpNqs1WmmLO4/RVbuvIha0vaf/b+MapNj6YfPsXOWTpvu35TVz5koz1JXrK+l6Yb4AUBhbpLtemhqyprsokwK7mhN3ImqD23zz0wRsWeM/ekztt2dzd3OH0tuOvxEzw0VqDquGRMg5dv7uW1O9d2dS2I+zojkaxEZEAmkUhWJXEZFEuen22DWba8OhNrUCMQiJY8t1BCUYKlQO6Zs0mbOgOZBKauEASC2brbEVPpSxtcNpwlZ5ld9+woitJRSA8/L91+2b21n9lqk+/sn6Zse+QsnZ/cMcjurd2baL/hmhFUAXc/PUnF9shaOrdcMcxPXzPS1bjtTNBEqcFMtcm63iSaquAHgort0Z9JdJ0JumZ9Dw8PZ3hqstp5uHHlUIZr1vd0Nfc2z83U+Y8jMxycPm0m7ouAK0byXb+fLsZ1RiJZSSjizCJdSSTK5TL5fJ5SqUQul1vu6UgklzRnGxSHxqEnSjZ9aVMah65SzmUiPFNzyFoGH7p1R+SMitwzCxMEgj/9+lN86+kpTE0loauhqEcATS/0xdpz5RC/97orI90Mx3lOITyvf/ntQxycquDP8abSVIXLhrK8/+btkc9rZ+zJCr4QhI8IFDRF4bLh7sae+zPaDwmaXihYsW0w03UmKO51b5uJz7TMxNWWfL8vBP3pBH/401cuSUZbIlnNLCY2kBkyiUSyqjjTOLTtVZO1DDIJnUPTVe55cootAxn5NHUVcaaJcNv7KWuppE2No4UGn31gjFdtX7PoniO5Z85D51cWmIaKoam4fkDT81vfjUac5xTC8/rF/zjKj48VMfXQcNrQFFxfULFdfnysyJcePBopmAwCwRcfbI2tKWSTRmddKo1w7C8+eJTfjxiotokjExT3us81E0/oGpahdgIy2w04WbH5+HcPRx5fInkhIt8pEolkVSGNQy9N4jQRlnvm3IwXGxTrocnvUC6J7QYU2ya/+SQv29RLMaLJb9zG0McKdf7jyGwoPJI2SegqqqKQ0MOxVUVh77OzHCvUFz328UKd/3h2Bk2B/kyChK61xtbozyRQFXjw2RmORxj7TFRVYX1fih3DOdb3pbp+KBD3uj98dJbDbTNxUw2tElqWCSlTRVcVDk1VeTiCmbhE8kJFBmQSiWRVcdo4dOEEf9LUaHq+NA5dZVyIibDrB5FMhC+VPRMEgmOzdfZPljk2WycIuu84aK/NSE+Kl27s4eqRHNuHslw9kuOlG3pY25OMvDZzz6kQgqbrU3c8mq6PEKKrcwpw5FSNYsOhJ2UsGGjnUwalhsORU7VFj/3sqRqluksuFaoczp07QD5lUGy4PBth7LiJ870EcHi6StMLx19o3cP3U8Dh6Wqk8SWSFyKyZFEikawqpHHopUmcJsKXwp6JS5CkvTYTxTonSk0KdQfPD9A1lfGizdp8IvLatM9pse7QdAUNN5R2VxWFpKGRMJSuzb6VlunxwnQXsAoFmm7AbNU9a+6pxOKl9M/FUit/xm3IbekaigJ+IFjIL9wPBIoSHieRSC6MlfvXRyKRSBagbRy6b6JEJqHPe0LbNg7dOZqXxqGrjLaJ8MHpCmlTm1dq1TYRvnwoG8lEeLXvmbMFSZLUHY99EyUmSo2uBElGe5L0JI1Q1KPdh2XpuL5gumJzvFBnz5VDkdZm1/peBrMJnjpRJqGrJAwNTVHxhaDadJmpBVw1kotsDL1lIE0+ZVCuu1g57azzWqq79CQNtgykFz325oE0SUNjothAU5Wz5l5sOAzlLDZHGHsuh6crfHPfJE+Ml6g7HilTZ+dontdePRz5nMb5XgK4dmMvmYROtemFIjBnrHvd8claOtdulCbuEsmFIksWJRLJqkIah16axGkivJr3zJmCJFnLQFMVspbB9sEMszWHe56c6q58sf1rd5QECT+3RJijjqyqChv7U6hKKLThBwIhws+uH2abNnTRM7WuN8VPbOnHF3Cq2qRiu1SbLhXb5VS1SSDgui39rOtNLXrs0XwYqHpBqKwY0l6JUJ6+N2Uwmo8exLdVHP/tsQkOT1eZKDY4PF3l3x6b4C+/fYjD05VI48ZtyL2hP82N2wdQVYVi3aXpBS1T64Bi3UVVFW7ctoYN/d0FqxLJCwmZIZNIJKsOaRx6adKWyf7M/WOMzdSYrTktE+Est12/qSsZ7dW6ZxYjSLK+b/GBx1xRj8lSk9m6Q63poakqQ/kkw7lER9RjseOHQiAKu7f2cXCySrHh0ggEmqrQnzG5bCgDKJHnrqoKv3jdBp45WWPfeInpSpMgEKiq0jm3v3jdhkgB34myTW/aZChnUW64ON5pw2xVgaG8RU/K5ETZjjT3uFUc43wvqarCHa/ZxmzNZd94Cdv1qTfDdU+ZOleP5vnV12xdkQ84JJKVigzIJBLJquRiGIcudW/HxWS1zv2mK4a4YXM/X370KOMFm9Feizfv2oBldf/nattglg03prhn/ySTpSbD+QR7dgxjnkP8IAqO4y/p+KcFSRbOxCRNjamyHVmQpD3+loEMI/kkz5yqUm36ZBIaWwcyCAXGTtUijd8ee8dwnssHs+w7UaZiu2Qtg6vX5kBVIo89l6yl05MyOFnxCQgDpt6UQaaLPVNzPExd5fqtAzwzXebYbIOmH5DQVNb3JdkymKXccCPPfa6KY2/KoFD3cIMAQ1XpTRmcrDodFceomaa430sffv0V3PXEJA+NzVJtemQSOi/b1MetO6OXW0okL1RkQCaRSFYtbbnoOIhLROFisJrnfu/TU52n+q4fYGgq337qJG+/obun+uca+8s/PL4kYwN8fu8Yn7zvCCcrNr4QaIrCndmD3P6Kzbx196ZIY8YtSNIe/8BkmQOTFYoNF7+VxXpyvMzlw1mylhFp/PbY+ydLnQxZe+wjJ2tcNpwhZ5mR594u5/zxsSLHCnNk+V0o2zWaXhDZX6499+lKg4miTdn28IWgqQRMFG2ySaOrubdVHAWCJ8bLOP7pwlBTCzOIbRXHqAFZnO8lCIOyO14T70MxieSFggzIJBKJ5AziFFGIm9U893ufnuKjd+2nYrv0p02SpkbD8Tk4XeGjd+0HiHwjGefYEAZjd959gGZLXj+hKzQ9wWS5wZ13HwCIFJTFLUgy2pNEIHjg2RlEIEgl9I658qlqk5lnHW65cjjS+OG/Eex9JvSjMnUVU1PwRSjNvveZWW65KppgCIQlkf/8yLH5wdgcjhUafOXhY/z0i0cW/eDmzLknTQ1DVXADwWzd7XruANWmR6XpIUSY1VMIu9QcXzBZbpJNRL9Fi3u/t4nzoZhE8kJCinpIJBLJHC6KiEJMrOa5e17AZ+4fo2K7bOhNkrUMdDVU/dvQm6Riu3z2gTG8Ob08K2FsCMsUP3nfEZqeT1/KIGVqaKpKytToSxk0PZ9P/eAIjuMveuy4BUmCQHB0JvQ0M3UtNPkFNFXB1LXw9dlapD0TBILnZup4gcDzA+qOT6XpUXd8PD/ACwRHu/BTmynZHJl5fmPmIzN1Zkp25LkHQmBoyjzzY0NTCER3c1/Xa1F3PAIBmhKut6qG42sKBALqjse6XmvRY8e93yUSydIjAzKJRCKZw2JEFFYaq3nujx4rMDZToz9tzpPpBlDV0DPpyKkajx4rrKixAe7ZP8nJik3K1BccP2XqTJdt7tk/GWn8tiDJ1SN5inWXsVM1inWXnaP5rjOejx4rMF1pMpK3yCQ0PF9guwGeL8gkdEbyFlPlZuR1Hy82SOhhMKMACq3PioKpKRwvNCKv+1efOL6kx82lsy49FpmEgeeHPmqeL8hYBiM90dcF4KkTFdqxnCAUtJz7GcKg7KkTi1danLvfFUWZZ2qtKErX+10ikSw9smRRIpFI5hC3iEKcXKy5xyEYMlNzcP2A5DkEMJKmxmzNYabmrKixASZLTXwhSOgKQoTGuAKBQpjxSOgKdUcwWWpGGh/CoGzTK9M8eqzATM2hP22ya31vZOnyNu21Gcwl0RQFxws6/W+mHvpujRcakdbmZKVJ1fbQVehLG/gBc9YF6k2PatPjZCXaukwWL+zfXehxc4lzXQCmy80wG4bADyCYG4kB4VZVmC5HnzvARNE+y9Q6l9Rx/SDy3CUSydIjAzKJRCKZQ9wiCnFyMeYel2BIf9rE0FQajk8mcfYNcMPxMbQwm9XN2Fnr7ACmm7EBhvMJNEWh4fgEwscLBEKAooCuKqiApigM5xORxoeF1/2hI4UlXfesZZAw5getjaYXeW0EgkAIFFXrBKqBCFAVFVVRUFSVwPUREZ3OBnIXNqcLPW4uca4LhHtGVxUMTSUQYd+YEKKTOVQVcH0Rac+05zRRbITj6WrH1LrmeFSbLpahRZ67RCJZemTJokQikcyhLaJwomQjxPwbxbaIwrbBTFfN/HER99zbgiH7Jkr0pAy2DGToSRnsmyjx6fvHIhvZAuxa38um/jRT5SbjhTrHCg2OFxocKzQYL9SZKjfZPJBm1/reyGPP1ByCYH7fTBCEmYKoYwPs2TFMT8qg0vRpegGqoqBrCqqi0PQCKo5Pb8pgz47hSONfjHWPY202DaRJmjp1x+NUtclszaFQ95itOZyqNqk7HilTZ9NANBXB216++bw3MWrruMVyMfbMmqyF7QVkEho9SYOelEFP0iCT0LC9gMGcFWnPXDPaQ0LXaLg+lq6gq0rn4YClK+H3DY1rRnsizV0ikSw9MiCTSCSSOcQtohAncc49bsEQXVfZc9UQrh9wquYQtEoAAyE4VXPw/ICfunIoUomerqu8/YZNZC2Do4XGvHU5WmiQswxuu35T5PI/XVe5YiSHqij4gcALAoQIP/tBWCp2xUg+0vgXY93jWpu8ZTKQMXE9gRtAQFiVFwBuAI4n6M+Y5K1omZqtw1l2rss/7zE71+XZOrz4DGLce8Y0NW5/xWYSusZs3cXxA1QFHD9gtu5i6RrvunFzJA+7qWrY+2YZGmU7fEgQBIKmF1C2fSxDZ23eYqoavYRWIpEsLSuv5kYikVxSxGlQHNfYbRGFOE1PPS9Y8n6guXP/xo8n+M7+acq2R87S+ckdg7zuxSOR5z5XMEQImCjVaTg+SVNjbS45TzAkigx2EAjKDY/tgxmmSg2mqw7lRuhZNZgxGconqdgeQSAineO2xPenf3CEg9MVHC/A1FUuH8ry9hs2dyUBPl5skLdMXrapl6cmSlSbPo4nUBXIJHSuHMmRs4xIazN33V3XZ++RGUoNj3xSZ/fm/q7XHc69NpcNZXlHF2szlElQsd3nLUis2i5DmWilnKqq8LH/8mJ+5R8f5Znp6ryfoyiwbU2Gj/2XF0e+JsS1Lm3aNgif/P6zTJZtKrZolbZa3P6KLZG962qOR2/a5MZta3h07BQzdYcgAFWFgbTBNRv7UVrHdctqNaCXSFYaMiCTSCSxEadBcdzmx8/N1Hnw2RmeOVnF8QNMTSUIBFeO5LoefyHD1k396SUzbP3Xxyb43ANjVGwPQehvNDZTxxPwW3sujzRmWzBkuuzz+PHSPJPfnqTRyVREvclrBx61psd4qdm5ufZ9wXipSdoyug48ICzdnKtotxQWAO216U+bZC2D5pz+t6yl05c2aXp+pLVpj/39gwWeOVmfF3T8+HiZrWtSXD6cW5qbaxFK0XuBQA3EWaV6i+XR4wXKttfx1zoTBSjZHo8eL/ATWwYi/Yxtg1k+8V938bUfTXD305NUbI+spfPaK4d5/TXRH0DMJQhC1UkvEKi+IPCXTi5+pCfJaK9FxfE6Ad9oj8VIFyXR7V7SZ05WmK17dNwWfJipeYwX6mxdk+26D3Y1G9BLJCsNGZBJJJJYiNOgOG7z43OZqh46WV3xBsUfu+cAn/jeM3iBwNRCNTs/gHLT4xPfewaIFpSlTZ1CzeGpiTJeIEKj3JaB8EzN4QeHTnHlSC7yTV7N8Xh4bJajC5j8CuDAVJWGEy2ogfnrviab6Kz74VO1rtf9zLUJ5e8VgkBQqLtdrU3a1Pnx0SLjC3hpCeDwyToNJ+jq5vrep6f44689xWytiaYo6GoYCD8+XuaPv/YUEG1tDk1VsV2fc4UvAWC7PoemqpEDMgiDsvf91GX8/MvWL2mmpr0uM511UfACwY8nuluXueO39+RwzursyWdO1bvak6M9SU4U6zx+vIwg7E1RW95mTV/w+PEyKVPrqg92NRvQSyQrEdlDJpFIlpw4+17i7qlZzQbFtu3xuQeeC4MCvaWupqqYukpKD28mP7/3OWx78UHNUCbBRNHG9nxylkZCD5XyErpKztKwPZ8TJTt6+VkAx1vBmEJ4A9n+aN9WHy80UCMsTdzr3l6buuujEPpVVW2PRuvruht9bfKmxsR5jI0nSjb5CL1GEK7N3/77YU5WbHQFLFMjZRpYpoauwMmKzd9+93CktTFUhfP9My8Ij+sWVVVY35dix3CO9X2proOxuetitEy+2x+GqnKyYvPxiOvSHj+uPek4Pvsmyp3suKYqKC3T6Xa2ct94OZJROaxuA3qJZKUiAzKJRLLkxGlQHLf58Wo2KP7yo0epNl1MVVlwfFNVqNguX3706KLHfmy8SNPzSZk6tida0u7hZ9sLs0K26/PYeDHS3L/x5Hgnk3LmrXT766B13GKJe90fGy9Sa7oohBkIAK31Y5q+QCHslYqyNv/z3w+eVxRetI6LwiNHZzk0XUVXFVIJY54iX/vrw1NVHjk6u+ixLzSbuRI9/R4+Osvh9rqYahjMKGFQkzJVdFXh0FSVhyOsC8S7J7/86FHqjo+pgqEpof1AyxvP0BRMFeqOH+k6AKvbgF4iWanIgEwikSw5pw2KFy6jSppa1z01cYwNF2YiHNVUNc6xAcYLNoE4HQyciaaGZUvjhefPuCxEe05reyzSpobnC2w37K1Jmzpre6x5xy1+7qcV30T7P60PcY7jFjP3ONf9ZLWJ7QUkNJWErhIIgeuHHlyWrpLQVGwv4GQEVbvjsxd2ri70uDM5OFXF8QIsI9w0ni9w/fC8AliGStMLODhVXfTYsxe4nhd63PMRBIJjs3X2T5Y5NlvvOjtzeLpK0wv3zEJBR3idCTg8vfh1gXj3ZPs6oGthljyhaySM8LOpq+iaEvk6APFfgyWSFyKyh0wikSw5cRoUx21+HKeJcNwGxaO9FqoS9owtFJT5QVgCONprLXrs9twRoRDBmcbN1S6Nctf1hXNSCBXy5tqoKa06KzHnuChzj2vdhQgzELqmwplCGEKgqCq+H5zlDXchXOjvG2VdACxDQ2mZENuue7apdStjZhmLL4nMJ81OdvNcoh7t47ohDnEJSw/XxQ8EC/3qfiDCddGjlYrGuSfPvA6E8eTpoLKb6wBcHAN6ieSFhsyQSSSSJSdOg+K4zY/jNISN22z2zbs2kEkYOAso5AVBgBMIspbBm3dt6GruQggShkbK1EkYGkKIruf+7uu3ktDUsO9FgK6GN5O6Gn4tgISu8u7rt3Y19zjWfVN/GkPXqDs+TiDQVQVTC0UgnECE5WO6xqb+xRsg/9ZPXn5+82MlPC4K127qxTI0KraPc4apteMFVG2fpKFx7abFr83NVwySNMPZ60p4w6EQftZb8UHKVLn5isFIc4f4TLOv3dhLJqFTd/wFrzN1xydr6Vy7MdqeiXNPxnkdgPivwRLJCxEZkEkkkiUnToPiuI2b4zSEjdts1rJ03nb9RnRVoe6JMIsVBDheQN0TGKrCW3dvxLIW/+Q67rmnUgY/f+268Mk+4VN8IcLPPmHQ8fMvXUcqdfYT+UXNfbbBbK1J2XaYrTU5Otv93LOWQc7SUAjVCcNqubAszG+V/mUtfcFswvlIJQ22D2We95jtgxlSycWPDbC+J8XavAVKOO9AhL2BgWj9HopgbY/F+p7FWw1sGsiwe2s/mqq0SujA0hV0jVZprcLurQNsGnj+3+9cxCkusaE/zY3bB1BVhWLdDc2VRWiuXKy7qKrCjdvWsCFCkA3xvp/ivA5A/NdgieSFiMwnSySSWGgbFLdLiabKNgldY+donj1XdedTE+fYcFpquu0VNltzMLTQRPi267vzCotzbDgtaf+5B56j2nRx/DCYyVsGb929MbIP2cWY+5/97E4A/vnh4zT9oFPnltBVfv6l6zqvR537RLHBJ+87wnih0Sm3XJOzeNvujV3NXYGO/5jt+NhegCfCkrZUQscyVHKWfpZYyYUwXmxw1UgexwsYm5nvQ6YAG/tTXDWSj+zPdqJsM9KTpFh3ma07eEErHamEPUi9qQRr80lOlO1Fj6+qCh+69QpK9Sd4cqKE44c+Z2EJpMpVI3k+eOuOyDfuixGXiDL3O16zjdmay77xErbrU2+GpuQpU+fq0Ty/+pqtXQUdcb6f4rwOQPzXYInkhYYiohS1S86iXC6Tz+cplUrkcrnlnk5sBIFgvNhYUq8XyaWN4/jcs3+SyVKT4XyCPTuGMSNKdJ9J3PvRtj2+/OhRxgs2o70Wb961IfJT5Ys5dtzjx3lOAU6V6tzxf37EiVKTtfkE//stL2EgH90MGk6Xtk2XGpysNWk4AUlTZU06wWA+2ZVv0v7JMv/9G08zU2tiO0HYA0cYMAkBlqnSn07wu6+7gh3Di/v7sH+yzF/fe4gtAxmaTYdvPDlJtemTSWi87qphzITB2Kkav3bT9kWPPXf8nqTBwRNFDp9s0PRDgZLta5JsX9tDqeFGHh/Ctf/aj47z9SdOGze/fucwP/2SdV3duM9dG4TgmVNVqk2PTEJn60AGodDV2rTn/v89foIfHD7VmfuN2wb4Ty9au2RBh+cFPHqswEzNoT9tsmt9b+Rs7ZlUaw4f+84Bjs/arOuz+K2fvJxMxF7JhZD3BBLJuVlMbCAzZJILJo7Gacmlzb1PT3We/rp+gKGpfPmHx3n7Dd1nU+C091AcLDT3bz91cknmHufYbSxL57brtyzJWHNZ6Drw3KnGkl0Hfu//PnE6QwYcnW1ww198j5+/NnqGrF3a9qNjBcZn6tRcvyNckTY0RvtTjD6ZZMtAJtLNZNrUGcgkGMiYTJaazNYd/CBAU1X60ibDuQSgdCVic9+hk+w/Ue7I6pdtn889eIwda3NsXZOJLKDQHv/JiRL7T1Q74zfcgMcnqjhCYeuabFcCDXufmeGrPz7BVKWJHwjKTY+v/vgEA7lkV3umPfdHnpvlqYkyNcfrnNcHzBmuHMmxNp/sWlxCVRV60yYJQ+2Yfi8luq7y8s39SzomnH2d2T9Z4fBUfUmvM3FegyWSFxIyIJNcEO2ny7M1h7V5i5SZpO547JsoMVFqdPV0WXJpcu/TU3z0rv1UbJf+tEnS1Gg4PgenK3z0rv0AS3ZTsNTEOffVvC5xXwd+7/8+wZd+eJRAtAQgWmqLTT/gSz8MPZOiBGXjxQb3PDXJ4alqSzUv9JPyA0HV8Tk8VeVudZKffvFIpJvLtsjBvokSL93YQ7Xp4/gBpqaSSWgcPllj52g+sojNRKnO48dLCMJ1UZWwB6vpCx4/XiJlapEFFEZ7kpwo1nn8ePkc45e7Gv/ze8e48+4DHQ+7hK7Q9ASTZZs77z4AwFt3b4o895Lt8NBYASHOOK9Nj4fGCrz6cj3y3Ofu99GeJClTp+54PDlR5kTJXtF/91bzdUYieSEiRT0k5yXOxmnJpYnnBXzm/jEqtsuG3iRZy0BXVbKWwYbeJBXb5bMPjOF5wfkHu8jEOffVvC5xXwfqdZd/fvh4KP7Q6l/S1FDxT28FCP/8yHHqdXfRYxdrDgenKviBwDJUDE1FVRQMTcUyVPxAcGiqQjGiH9ZckYPDJ2soCvSkDBQFDp+sdSVy4Dg+T46XOyWQmqqgqOHatNwAeHK8hOP4kebuOD77Jp5//H3j5UjjO47PJ+87QtPz6UsZpEwNTVVJmRp9KYOm5/OpHxyJPHfPC3h6okwgBJqqoKlqy7xZbQmJCJ6eKEV6P63mv3ur+TojkbxQkQGZ5LwspnFaIgF49FiBsZka/WkTVZ1/mVHV0FvnyKkajx4rLNMMz02cc1/N6xL3deDvHniGph+EGZozAhdVVVCBphfwdw88s+ixHz02i+MFoa/WGXNXlVCevukFPHpsNtLc4bTIwdUjeYp1l7FTNYp1l52j+a4yKV9+9Ggom6+CoSkIQs8zQZgRMlWoOT5ffvRobOPXI45/z/5JTlbsVpnf2fs9ZepMl23u2T8Zae737J+kWHfJJrSOIbfXMuRO6BpZU6NQdyONP3e/A5QbLqeqTcqN8IHASv67t5qvMxLJCxVZsig5LzXHw/Z8UubCZR9JU2OqbFNzvIs8M8lKZabm4PoByXMIPSRNjdmaw0zEjEScxDn31bwucV8Hjs/aAB1BDCFOGxQritIxh24ftxiaXpjFEJwW22jT/t7c46KybTDLpleml1SgYbxgEwhI6AqKouC17ADaxs1CgOsKxguLX5czx1dVFSFAIFAI1zwIgsjjT5aa+EKQ0BfODCZ0hbojmCw1I829PX7O1Fu+aWEwpioKph5myOy6G2n89n63XY2nTxQo1B08P0DXVHpTJpsGUjQ9f0X+3VvN1xmJ5IWKDMgk56XdOF13vAV9dBqOT0LXum6cllw69KdNDE2l4fhkrbNvRhuOj6GFT2pXGnHOfTWvS9zXgXV9YSbCn+PdBbSiJXHWcYthpMfC0FREK4OiqUqnP80PBApgaCojPYsfey6Hpyt884lJnhgvUXM90obOD0dnee3O4cgZstFeC1UB1xP4tD3OQlxFoBH2fI32Rpt7e3w/CI24wwTi6QDKD6KPP5xPoClhz1hqgS3d9ELrgeF8ItLc2+M3HJ9AKHhB0AlWm56KqkQfP23qOF7AI8/N4geCjGVgWDquLzhZsZmtNVnfl1qRf/dW83VGInmhIksWJeel3bB+omRzpkuCEIITJZttg5nIjdOSS49d63vZ1J9mpuYQBPP7FIIgYKbmsHkgza71vcs0w3MT59xX87rEfR149/VbMc7zF8lQw+MWy54dwwzlLAJAV5lX2qarEADDeYs9O4YjzR3CYOwvv32If3t8gsMnq5wo2hw+WeXfHp/gL799iMPTlUjjvnnXBhK6iivCPjqF0x+BAFeApau8edeGyONnEgZOIAiCIDSzbplCB0GAEwiylhFp/D07hlmTtag7HkEQ4PkC1w8/B0FA3fEYzEVf9z07hulJGVSaPk3PC8tPtbAstel5VJo+vSkj0vhrcxZNN6DYcOlNGST0sO8woav0pgyKDRfHC1ib6y6Ij4PVfJ2RSF6oyIBMcl7mNqwfmq5SsV28IKBiuxyarnbVsC65NNF1lbffsImsZXC00Ji3Z44WGuQsg9uu37RkXjtLSZxzX83rEvd1wDS18z6xH0ibkfzOTFPj9ldsJmlouL7A1FTSCQ1TU3F9QcrQeNeNmyN7qQWB4Iv/cZQfHyvitwKYvrRJ1jLwA8GPjxX50oNHIwlA6LpKf+b0uogzPgP0ZRKR94xl6bzt+o1oikLNFdQdn4YTUHd8am6YYXrr7o2RPOza625oGtMVh0KtSbEefp6uOBhad+uu6ypXjuRQFQU/IMyQBQIvCFqZPYUrRnKR1uZE2SZhhMFXoe7S9HwCIWh6PoW6S0/SwNRVTpSjlYrGyWq+zkgkL1RWXq5dsiJpN6y3/YemyjYJXWPnaJ49V0kfMsnZtCWV2z44szUHQ1O5fCjLbdcvnQ9OHLTn9qnvP8P+qWpHwvyK4QzvfMXWruZ+sdYlDvPm9nXgricmeWhstmPC+7JNfdzaRVkehEIEhq7Rk9QpNs7uy+lJ6ui6xqPHCpE8m9rS6p/8/rNMVZo03LDXaDhvcfsrtkSWXgc4VqjzH0dmURWF3qROoe7iBAGmqtKb0jlZddn77CzHCnU29qcXNXYovKAwkDaZrTkEnA7GVKCvFcRGXReAN1wzwnf2T7F/soI/J6Giq3D5cIY3XDMSaVyA3Vv72TGc4cmJMo4fhOlIBUxdZcdwht1bo/tvjRcb5CyTl23qYd/xEjUnwCEsQU0nVK4ezZOzTMaLjUXbGdQcD1NX2bWhl7FTdWbrDrWmh6aqDOYsNvWnKDXcJekhi8MYejVffyWSFyIyIJNcMNsGs2x5dYbxYoOa45E2Q38XmRmTnIubrhjiVdvXLPnNxsVgothgvBiKVPhBWGp1vGAzsQSqanGvy+f3jvHJ+45wsmLjizDLcWf2ILe/YnNXgQfAczN1Hnx2hmdOng5Ug0Bw5Uiuq4CsI0RgaAsGZJah4vpBV0IEu7f2U6g1+cHhGSq2S9YyuHFbf1dBAcCRUzWKDQeE4InxBs6cHjhTU+jPmJQaAUdO1RYdkLXXJWWqlG1l3ti6ppA0u1uXtrx7XyrBrnUKz55q0PQDEprKloEklmlyz5NTkUyz22OvyVq88/penj1Vp+J4ZE2dLQMpnp1pRB4bTgtv9KUtelINPOHgBQJdVehJmvSmE5GFN9o9k5ahce2mXiq219nvWUun2vSw3aDrHrKFTOI39aeXxLx5NV9/JZIXGjIgkywKVVUiGadKXrjouhr5yf1ycU4z20r3ZrZt4lqXcxvxNrqe+7nMZg+drHZtNtufNqk5PhV74ZvnybJD1tIjCxHMNfm9ejTfMfl9erLKVGWsa5Pfmu1RaXqhqASnTa0dXzBZbpJNRPtz2582sd2AqXIot64pp42bXV9wvGCTTxqR12W82OBHxwocK9QpN1wEocBJADxzqkEu6ZE4qkbKMs2Vjtd1ncuGc/NenysdH+XvStrUKdQcnjpRxvMF6YSOoSq4gWC27nL/4VNcuTYXKWiaa/a9fTBDLnlayKbdMxnV7LvNxTBvXo3XX4nkhYh8TCKRSCRziNvMNk7inHvcZrNXDmapNZ8/k1FrelwZIWiK2+R3Xd6i7vgdBURBGDC1RwtE6OW1Lr94AYirh3I0HB9BGIyFCpGhcbPWsghouD5XD+XON9SCVJphD+BszUEACV0laagkdBUBzNYcDk9XqTQXb8h92ipBRwgxz8tLCEHS1LqSjh/KJJgo2tiuT84KvchUNRTeyFkatutzomQzlFm8ymLcPZPSvFkikcxFBmQSiUQyh7jNbOMkzrnHbTb7z48d53zxUCDC4xZL3KbWT01VCMRprzM4LRx/OigTPDW1eKXF7xyeRiDCrBhhcBmI0Lw5IMyWCSH4zuHpSHMvN1yKNScMkAx1XsCXNEKrgELN6RgiL4Z22d9Esc5DYwX2PjvDg8/OsPfZGR4aK3Ci2OjKKuGx8SJNzydpaNiewAtC7zovENieCL/v+jw2Xow0flxm3yDNmyUSyXxkyaJEIpHMIW4z2ziJc+5xm83unwyDlZb/81m0v98+bjHEbWo9WbI7htOC+WbTzPn+ZCmaubKiQNbSaTg+ni86ZZFhD1kYdETdj6GHVxjwzbfMDr9WCYPJRoSs6mhPkp6kwbeensLUw+xP28trumJzvFBnz5VDkcv+2nttpCdJueFSa/qdnsl0QiOXNLo2QI6rd1qaN0skkrnIgEwikUjmELeZbZzEOfe4zWZ7WxM+V5JMnHHcYojb1DqhK52+MX+BX6B9736uQPn5aJ9ThMDUwn8fBlBK+LXobj8qShjUeX5Aw/UxdRVNUfCFwPECNE0hoalnZRYv/AeEn0QQ0PR8XF8hEALR8seKViQa0t6TTc8//bPakTHQ9JbGADmO3mlp3iyRSOYiSxYlEolkDmea2c5lKcxs4yTOucdtNvtzLx097x8ktXXcYonb1HrX+j40VekEY3PNmyEM0jRVYdf6vkWPPdf82PFCFT7L0DA0FccLqDR9eiKaHwNsGUgzkElgmTopU8NxA6pND8cNSJuhyuCaTIItA4tTh4SwVLRYd7l8OIMXwHihwdipGuOFBl4QSuoX627kUtFd63sZzIZ9ZFXbxdRVMgkdU1ep2i4TRZvBXGJFGiBL82aJRDIXGZBJJBLJHNpmtgldY7buUnd8/CA0yp2tu1h6d2a2cRLn3OM2m12fS6GfJ0Gl6+FxiyVugYZMUu9kr2Bh82ZTU8kkF5+B03WVK9e2zI8FeH7Q+fBFaH58VUTzY4B1vSl+Yks/QSCoNz3cIMAPAtwgoNb0CARct6Wfdb2LX/ea43Gq2uREqYmhqQxmEwznEwxmExiayolSk1PVZuRSUVVV2NiXQlUU3AD8QCCECG0qWsbQm/pSK9KaRZo3SySSuciSRYlEIjmDjolwy8ur7oRlYWvzSd51Y/deXnES59zjNJv99sEpEOfqIGshFL59cIrXv2jxWbI4ze2nyzaqqmLqAZ7HfPNmBXQtzJBNl202D2QWNfZ4sUEuaXLVSJb9Jyo059REJjSFHWuzZCOaH0MY1NywbYC79k1Sdfwwg9gq+2sqCpapc8O2gUhBTdLQOFV1KNYdFMD2gk65paWrNFwfIcLjojBebICisHtrHwcmq5QaLo1AoKmh99tlQxkESuS1iRtp3iyRSNrIgEwiWQKCQMRqmB33+HES59w9L4jN9PStuzfxsy8a4WPfOcDxWZt1fRa/9ZOXk1kFPR1v3b2JN71kHV9+9CjjBZvRXos379qAZXV/yb/piiFu2Ny/5GNPFG38QGAo4J4RkymAroQZkIni4oUx2mwbzLLhxhT37J9kstRkOJ9gz47hrrOds3UXU1NRFY2GCDpqf4oCekutUFdVZuvRpONPVZt4gWBtLkHDC3ADgaEqJHUVLxBdZZmCQHD/4VMIIUib2llzFyJ8/TWXDy76fasATdenbLsYaqjgGI4Z2gC4QUDK1M6SErlQ2mItO4bzXDGc40TJpu76pAyNtXmLABg7VYu8Nm3ivIZJ82aJRAIyIJNIuubwdKXz1N32fCxdY+uaDLdc3d1T94s1fpzEOfd7n57qPFl2/bC3ZlN/mrffsDRPlj+/d6yTZWort33n6VPc/oqVnSGDs9f9VNWhao/Ftu7ffupk1+veFrw4MxiDMGHjitCHK4owRpuF5v7lHx7veu79aRNdU6g5AscXp3N8AgJfoHoCK6lEEmhIGRqnqmFpn+342F7QCZgaukrdC0CEx0XheKHOfzw7g6oqpE2NmnM6i5U2Qy+yB5+d4Xihzob+xfWRVZsefkuiv+F7zFfdCH+GFwiq5/GfOxdnirWMnlFWWbPdrsRa4OJcf6V5s0QikQGZRNIFh6crfPr+MWZrDmvzFikzSd3x2DdRYqLU6NqrJu7x4yTOud/79BQfvWs/FdulP22SNDUajs/B6QofvWs/QFc32J/fO8addx+g2TK1TeihcuFkucGddx8AWLFBWXvdZ6oOOUsnZxkEgeCJ8ZW97i/Z2LugQuFcfBEeF4U4537NaA9+IGi4oTiDpoQBkxDhnBtuQNYKj1ssAqjYLrM1F4TA0MNMkx8I6o5P3Q1I6FpktcJnT9XCDJwfIFBIGKdVFutugILgZLXJs6dqkQIy2/XRNIXAb/0y7XxYy+vMdv3IAVlbrGXfRIlMQp+nBNkWa9k5mo8s1rKar78SiWR1IXPiEklEgkBw974pZmsO2wczZC0DTVXIWgbbBzPM1hzueXKK4Hxut8s0fpzEOXfPC/jM/WNUbJcNvUmyloGuhh5HG3qTVGyXzz4whucF5x9sARzH55P3HaHp+fSlDFKmhqaqpEyNvpRB0/P51A+O4ETwZYqb9rofna1Tqjs8Pl7i4edmeXy8RKnucHS2vmLXXb3AkOJCj5tL3HOfKDVwvKAjfd8OC+Z+3XR9JkqLVxOsNjzKdhjN6JoSSui3fMN0Lcw0VWyPaiNaUCNaHmN+EBop66oyp9RSw/fD189Up7wQUqaG6wuCAHqTBvmkQS6pk08a9CYNAgGeL0hFLBmNU6xlNV9/JRLJ6kMGZBJJRMaLDZ45WWVt3jrLo0dRFNbmLQ5PVyNLOsc9fpzEOfdHjxUYm6nRnzZR1fmXMFUNfXuOnKrx6LFCpLnfs3+SkxWblKkvOH7K1Jku29yzfzLS+G2CQHBsts7+yTLHZutLcmM3Xmzwo2MFTlZsTlabWIZKb8rEMlROVptMl20ePVpYkev+v759eEmPm0vcc3/4uQKOH5AxVQxVIQCCIBT3MFSFjKni+AEPP7f48Y/MVnFbmVpTU8MgJoBAhMqNKVPH8XyOzFYjzT1paqiKQiDC4MzzBa4ftAyoBQGhWuG5DIyfj7rjY2gKpq5iewG0Aj2UUODD1FV0TaHexcONtljL1SN5inWXsVM1inWXnaP5rjJYq/n6K5FIVh+yZFEiiUi7oTxlLlwOkzQ1psp25IbyueMLET4Fd/wAU1PJWnrX48dJnGszU3Nw/eCcN4hJU2O25jBTcxY9NsBkqYkvxDl7lRK6Qt0RTJaakcaHsBTqm09M8sR4iZrrkTZ0do7mee3O4a5KoCq2y9GZOn4Q0J9JdG4kE7qGmVaZqTY5NlunYi9eXGLuuvu+T6EeSqQbqkpvSu963Q9NX1hAcaHHzWXu3EXL8LjdF2jqatdzt72WWqClk1GUMCskAlRFxdDC8r9yI3xPLBZFUVBVpRUUhQFZuwtLVaDhClRViWzcnEsa9KRNTlWazNYcBKdFPRQUdE2lP2OSS55tqH0+MpZOLmnQaPoEIvRM81sqiNmEhqqopBIamS4FYbYNZtny6sySCm/EfX2XSCSSuciATCKJyJkN5WfScPyuGsrb408U65woNSnUHTw/QNfCrMfafKLrhvW4iHNt+tMmhqbScHyy1tlJ/objY2hqJAEFgOF8Ak0Je8ZSCwzR9MIb+eF8ItL4h6cr/OW3D3FwqoI/Jyt2ZKbG/qkK7795e+SgrNr0aLg+2dYNbtP15wUeCUMLy9si9Oy01318tk6h7uLMafgyNYXelIGha5HXPZcyYOb82YZcavGBQXvuxbpD0xU0XL8jXJE0NBKG0tWe2TaYIaG396ROwlBpF6AIIWg0fRK6yrbBxUneA6zJJMgkdJpegO2JMKukhL1pthegKJBJ6KzJRNuP2YTBSN7iZNnGnStIAigINFWwNm+RTSx+3bMJgw19KZ4+UWam5rSybmGw53g+/ZkE6/tSkcY+E1VVllTaPu7ru0QikcxFlixKJBFpN5SfKNln9Ve0G8q3DWYiN5SP9iTpSRo8NFZgumJjGRq9aRPL0Jiu2Dw0VqA3ZUQeP07iXJtd63vZ1J9mpuYQBPN7foIgYKbmsHkgza710cQf9uwYZk3Wou54C45fdzwGcxZ7dgwveuwgEHzxP47y42NF/ECQtQz60iZZy8APBD8+VuRLDx6NXL6YaWVOK7bHeKHBsUKD463P44UGFdsjZUbLSOxa34upKUxVHBw/7GHSlDBL4/iCqYpDQlcir/sdr9q6pMfNZdf6XgazCSaKNtWmi66FgZiuKVSbLhNFm6FcIvLcr93Qx7bBDF4gqDtt2Xsx7+vtQxmu3dAXae7bB7OoCqQMFc8X2G5YUpgyVFQFLhvKRp772pzVyhiCqSsYmoKu0io1DM2oXT9gbc5a9NijPUlyCZ3ZmoMfhEGTrocZPz+A2ZpD3tJfcNcwiUQiORMZkEkkEYmzobxD+58KwWmrWdH6+nktdJeVONdG11XefsMmspbB0UJj3thHCw1ylsFt12+K7ONjmhq3v2IzCV1jtu5Sd3z8IKDu+MzWXSxd4103bo7kXXWsUOc/jsyiKqEEekJXURWFhB5mZ1RFYe+zsxwr1CPNPZsw6E+bVGyXYsNFUcDSVRQFig2Xsu2GAWCEjEQQCMq2R3snKgooLQGI9vfKth85mNw2nON8K6q1jlssqqqwsT+F2ion9FsBkx8IXD/MlG3oS0V+r+q6yq++Zhtrshau71NrelRsj1rTw/V9BrMW73n1tkh7sr3fe9MJ3EDQmzIYzlv0pgzcQNCXTnS138dLDYoNF1ML92E6oZOxDNIJnYQellwW6i7jEQRJgkDw3Gy4l1OGQi5pkLMMckmDlBGu9dgS9U8uNRfl+i6RSCQtZK5d8oIhDnPPdkN526dmqmyT0DV2jubZc1V3PjXjxQbFusvLNvUyWWoyW3eoNT00VWUon2Q4l6BYdxkvNpa0VGepaK9Nu1eq7nqkDJ0Xrctzy9Xd9Uq15cnbnlKzNQdDU7l8KMtt13fvQ9aWtP/77z/LdMWm2myVKeYsbn/FlsiS90dO1Sg2HNZkEp2+QC8I0FWVTEIjnzKYqTY5cqrGxkVKjEOY7dBbBrxpU8P2BE0vQFEUepI6thd6b0XJdtyzf5Ja0yOTUHG8UPxBIFAISxZNXaFqu9yzf5LXv2h00eM3XJ+hfIKJ5+nNG84naLiL78MKhRcUdm/t48CJCoW6S63Vy9SXNrh8OAsoXb2XbrpiiIlio7Nn2qWiQzmL21+xuas9eeZ+rzY9DE1lx3Cu6/1+5FSNhuvTnzGZrbnUml6nrNAyNAYyBrbrR9qTjx4rMF1pMtJjzSsVVRSFbCpBQleYLjd59FhhRfpwxXl9l0gkkrnIgEzygiBOc884GsrhdFP5loEM63pTZ4l6+EIwdqq24pvK/UBQqDtUbI+sFZZaLQU3XTHEq7av4dFjBWZqDv1pk13reyNnCs5k99Z+TpVt7nlqirLtkbN09lw5xO6t3d04KgKKDYdC1aHhBq2gRiFpqPRmovUwtTlRtkkYKgOZBJ4fkEu1FfQEjuuTSZqYusqJsr3owKMtdpLUdRChDHr7xj3MrmhUm15ksZOqHT5ssAwFewF3aMtQUFWVqr34/d5+Lw1mk1RtD0VROu+lkR6LNVmLcsPt6r10eLrC/skKVwxn2TKYxvMCdF0loarsn6xweLrS9UOIuPa75wfYToCmKuQsY46HmqDccNG1aD+jLaYymEuiKcpZYiq+EIwXGpHFVC4GcV3fJRKJZC4yIJNc8lwMc8+lbiiHs5vKz1Q5azS9Fd1Ufni6wp98/Wn2jZdoemEpm6oqPHOyxqPHinz49Vd0ve66rsbyZD2c+1PsGy/TbCnolWyXf/zhMR4bL/Hh118Zae5bBtKoCowXGgRzq1ARVB2feqHBSM5iy8Dis2MQBh6mrvLSjX0cOVWjUHdo+j56K6u6sT8VOfAYzidQUCg3XOZWmImW8XHTC9BUNbLYSSahU6g5CwZjALYrKNQcMonF7/e0qeN4AY88N4sfCPoyCQwtLF88VXUo1Aus70tFfi91/N9m6nhBQKHuzhHgMajPhP5vWwYyXd3Iq6rC2nySXNIgbepLEhRs6kt1zmFvyjjLXLlQd8lqKpsiXN/mC/AYJIz5RamNVqYvqpjKxSKO67tEIpHMZWXeyUkkS8SZ5p7tm42sZZBJ6Byari7JjVIctJvK902UyCT0s26UTpRsdo7mV2RTeRAI/ve/H+bh52YRgSCV0Ds3wPWmx8PPzfK3//4M/8+bXrzi1j0IBH/7ncM8PBZ6RiVNDUNVcIPQIPfhsQIf//fD3PmmaxY99+Gshe0FtP2HdTWUFheIjreU7QcMZxdfUging3jLUHnZpt6zsqrVpkfTDSIFHjdfNoSuhn5SbTGPNoEANwDLULn5smjlc5qA6nn8qKqOjxYhwbo2Z9F0A4qN0Bi67UWW0BWMVNiLOORFE66A0/5v0xUbPxBkLAPD0nF9wclKE01VOv5vUW/s48ryK2rY22W7PnXHJ2FoaEoo1d90/Y4ZshLhfdoW4Dk4XSFtavM84NoCPJd3IUgikUgklwpS1ENySbOazT1Xc1P50ZkaPzh0iiAQ9KSMeeIVPSmDIBD84PBJjs7UlnuqZ/HcbI37Ds8QCMhZobCBqoZzz1k6gYD7Ds/w3Ozi5/6j4wUaro/WUigUAoJW6V/7e3XH50fHoxkUz1WGg9BjaiCT6GRXu1GGm6o1yVgaCqHkejtLFojwawVIJzSmatFKFr/40JElPW4u7VLO3pRBoe6GGVshaHo+hbpLT9LolHJGodJ0OTpbx/ND0Q2EwHZ9EOHXnh+agFeai/d/g9NZ/n0TJXpSBlsGMvSkDPZNlPj0/WMcnq5EGhfC3r3RniRDOQtVVWi6AQ0nDNxVVWE4bzHak4zUuxe3AI9EIpFcKsgMmeSS5mKZe8YhGAKrt6n84ecKVJuhxPpCgXCqJc3+8HMFNq1ZvDdTmzjW/eGxAtWmu2BJmKq25+7y8FiBzQOLm/vBqSqeL8gnwxI62w0IRJhtsgwVQ1dpOAEHp6pct2Vg0XNvB/ETpQaHpsMHEUlTo+H4nCjZXQXxR07VUFWFkR6Lk5Umji9otwOamsJAxkRRlMiCJPsmLizAvdDj5tIu5dy1oZexU/V5AjmDOYtN/SlKXfSQVW2PhuNj6gonSjY157QBctrUSBgqdSeI1P8Wd5Y/beoMZBIMZExOlGymy82O4fdgLsHavAUokcs54xbgkUgkkksBGZBJLmkuhrlnnIIhsDqbyu1W35V2jjlqqoIQ4XFRiWvdbddviVUsXBunKmFGy46QMbAMDUUJsxKNOb1SgYCqE5BsKdBZxuIl9dvEGcSHS3LadqGDEHS7GzMLmHx3c9xcTpdyalx7jlJOO2IpJ4T9b5qqcKJoEwhBmC8MPzccD1VRGMxZkfrfFpPlj1IOObc0+tqNvVSbfmdtMgmNwydrXZdGxy3AI5FIJKsdGZBJLmni7sO6GIIhsPqayrcNZkjoYTO/bilnrXsYCKtsG4yWHWuv+0zVIWfp5KywDPKJ8e7X/bKhDKauYrsBhhYGUKfnDrYbkNBVLhta/Nyv3dSLAtTPIVzRcAUpQ+HaTd311MQRxG8ZSOMLwWT57JJEJ4DxUpPhXCKyIMn1m9fwvYOzF3TcYpl7Hdg+mJknkLMU14FMQscPBE7LYkBTw2BJCPAD8EQQ9pZFCMjmZvnbVglzg8lus/xzs6qHT9ZYm7foSRk0HJ/DJ2tLVhodlwCPRCKRXArIgExySRNnCddqFgyJm2s39LFtMMNTJ8rUnQBdVVAUgRAKXiDwAsFVI1mu3dC36LE7inazdTwvYGym1vHy6k0a1Byvq3V/6YY+trfn3nRJmPppkQPHwwsEV45keWmEuQ+lErjnkf13fcFQKppS4VyWOogfTCco28/fA1WxXQbT0ea+tvfCBDUu9Li5zL0OHJyqkrXCjJYfhAFOf6a7oCNo9YypqoIQAscX7QRZKICiKp2+tcXSzu5NFOucKDUp1J05Co4ma/OJrrP8q7U0WiKRSC4VZEAmueSJ62Yj7lKi1Yyuq/zqa7bx+1/dx0y1GXpWERZyKYrCQCbBe169LVLJUlvR7mTFxvMFGUvH0HRcP+BktXtFu/bc//hrTzFbayIcvxNM+gIGsxa/GnHuX3nsGH7w/DflfiD4ymPHuO36LYseP06+dWAK2w2e95iGG/CtA1P89IsXbwyNUDqFfudCaR0XhW2DWX5yxyCfuX+MJydKuH5okr2pP82brl3XVdAxNlPHD0TLv0vB0ELFrAAIgtCrzfMFYzN1Ni2y73C0J0lP0uBbT09h6irZOQqO0xWb44U6e64c6lptdTWWRkskEsmlggzIJIvC84LY+gDiEsaA8GZj0yvTSzr3uaVEQRBwomRTd31ShtbJxC2FYAjEu+5xjb2xP8VlQxmecH3qrtcxEU4ZOtuHMmzsjxakVmyXozN1/CCgP5PoBMMJXcNMq8xUm6Gi3XmyOc9HW2jg0/cf4ZmTVVxPYOgK29ZkefsN0YUIxgs2ArB0haYn5gUfCqEMe9MTjBeiqf3NZanP6/7JckdZsR1stOkEHyI8LkpAVvcu7H1yocedyeHpCt/ZP03SUNm2Jt0p+zM0le/sn2ZjfypyUCaECAM8VUEogqYn8Dh9ThUUXD9ARMiQQWug8AfRSb3N6eVbGqv1eEuj47y+SyQSyWpnWQOy73//+9x555088sgjnDhxgv/7f/8vP/MzP9N5XQjBH/7hH/L3f//3FItFbrjhBj7+8Y+zffv2zjGzs7P82q/9Gl/72tdQVZU3vvGN/NVf/RWZzOmnkI8//jh33HEHDz30EGvWrOHXfu3X+J3f+Z15c/nKV77Chz/8YcbGxti+fTt//ud/zn/6T/8p9jVYTdz79FRHKWvu0+VublDbxC2MsdD4Dx0pdDV+u5Ro/2SJg5NVig23o6zWkzS4bDhDzjK7Nm6Oc93vfXqKT/8gDDraN6hb12R4x42buxq7XVYYCNi+Js1EudkZfySXIBBELiusNj0ark/W0hfMTCaMUMGx2uwuEI5DiGC010JVwPbOvoUWhN/XlPC4bohjzwStCExhfjBG6+t2dit4/iTaOfF8ga6GfmbnQlfD4xZLez/unywzXbIp2V7nvZq3dGbqTldlrklTQ1UU6p7PmVovniswNEFKC/u9Fst4sUGx7vKyTb1MlprzFCKH8kmGcwmKdXdFZ+Ljvr5LJBLJamdZJY5qtRovfvGL+d//+38v+Ppf/MVf8Nd//dd84hOf4MEHHySdTnPLLbdg26efHv/SL/0STz75JN/61rf4+te/zve//33e/e53d14vl8vs2bOHjRs38sgjj3DnnXfyR3/0R/zd3/1d55gHHniAX/iFX+Bd73oXP/rRj/iZn/kZfuZnfoZ9+/bF98uvMu59eoqP3rWfg9MVspbOaG+SrKVzcLrCR+/az71PT0UeO06PnTjHD0uEBHufmWWm5mC2fKpMXWWm5rD3mVlAdFVKFOe63/v0FH/8taf40fFiR6a75vj86HiRP/7aU12NPbescKbu0p8x2dCXoj9jMlN3mS7bnbLCxZJpCRk03bMzDkIImm5AytTIWN0/b2oLEdx69Vpevrm/68zhm3dtQDnP/b6ihMdFpbNnpipYhkpv2sQyVA5OdbdnXrKx53lLCtt5m5ds7Ik0/rbBTMcw+1x4AZGEYMaLDX5w+CTPTFeZrbsogKGFJZKzdZfD01XuO3Qysh9hLmkg4KxgrI3rh+szV0zkQmln4kd6Uly7qZfdW/p5+eZ+dm/p59qNvaztSdL0/CXJxMdB3Nd3iUQiuRRY1oDs1ltv5U//9E/52Z/92bNeE0Lwl3/5l/z+7/8+b3jDG3jRi17E5z73OSYmJvjqV78KwNNPP803v/lNPvnJT3Lddddx44038r/+1//i//yf/8PExAQAX/jCF3Ach3/4h3/gqquu4i1veQu//uu/zv/7//6/nZ/1V3/1V7z2ta/lt3/7t7niiiv4kz/5E3bt2sXf/M3fXJR1WOl4XsBn7h+jYrts6E2StQx0Nexl2NCbpGK7fPaBMbzz3U0twJnCGFnLQFMVspbB9sEMs7XwyXVwnr6b5Rg/CATPzdQJhMDQFDRVaSmsKRiaQiAER2frkece57p7XsDf/vthTlZsDFUlZWqdD0NVOVmx+fh3D0caG06XFbpeQF/aJKFrLWNojb60iecHkcsKswmDDX0pdE1htubMM/mdrTnousr6vhTZxOJvfuPG8wP88yypH4THRRq/tWcKNQddhdmay2TJZrbmoqtQqDmR98y2NRn08yR4dC08Lgpb+pLnLb0TreMWS6nhcHCqSsPxcTyfStOj3PCoND0cz8d2fA5NVSk1nEhzNzXlvAFR3fEwtWg+YW3rDkVR5pl9K4qyJNYdcRH39V0ikUguFVasCciRI0eYnJzk5ptv7nwvn89z3XXXsXfvXgD27t1LT08P1157beeYm2++GVVVefDBBzvHvPKVr8Q0zc4xt9xyCwcOHKBQKHSOmftz2se0f85CNJtNyuXyvI9LlUePFRibqdGfNlHV+VtGVVX60yZHTtV49Fhh0WMvRhgjCnGO/+ixAtOVJiM9FpmEgecLGq7fEpowGOmxmCo3I61Le/y41v3ho7Mcnq6iqwopU50XTKZMFV1VODRV5eGj55chX4h2WWHCWNgYOmFo1B0/UlnhaE+Sl6zvZTBrsSabwHYDCnUH2w1Yk00wmEmwa0Nv1yIHcfCx7xy4oKDjY985EGn8R48VODRdwQ8C6m6ArikkDQ1dU6i7AX4QcHCqEmnPTFeamJp2Tr8xBTA1jenK2bL4F8Jv/8sTS3rcXMZmalRsNzSzDkIjbk1VUJUwAHZ8Qdl2GZtZvOk0wH2HTp030PaC8LjF0pbsP1GyF8wInyjZbBvMrMj9Hvf1XSKRSC4VVmxANjk5CcDQ0Px+h6Ghoc5rk5OTDA4Ozntd13X6+vrmHbPQGHN/xrmOab++EB/96EfJ5/Odj/Xr1y/2V1w1zNQcXD84Z/9D0tRw/YCZ2uKfLp8Wxlj46W7S1Loqx4lz/Pa69KRMRnos1vcmWdebZH1vkpG8RU/KjLwuc8dPmlqrFM+n7ng0XR8hRFfrfni6StMLx17oRilcl4DD09VIc4+zrLAtYb6hP0XOMtgykGbbmgxbBtLkLIMN/akl8U2C8An/sdk6+yfLHOsi29nm+OzpcuszL77qOY5bDCerzTDIFYSBmKqgKKCrYWCGCIPlk9XFB02FuouhKZyralNXw0xRoR5NTGWieGG/84UeN5dAhFYLAlDVdr9baGatqmEQ7AUikiw9wHjhdEChLPCx0HEXSnu/96VNDk1XqdguXhBQsV0OTVeXzCcsDuK+vkskEsmlwsqrcVglfOhDH+I3f/M3O1+Xy+VLNijrT5sYWmjym7XOvhtrOD6GFmZsFsvccpysdXaJWbflOHGOP39dDBLG/IC10fQir8vc8Yt1h6YbZt8CIVCV8OY6YSiRx7f00PDYDwTGAnF2W8LbOl+N2jlolxUem60zW3Na0vQqrh9Qtb2wrLA3GbmscK6E+ZnCFT+5YzA2IZhuhQjW9c0R61AWeCImFjhuEQghCAKBYqhn9aopCiiqQrBAkHwh9KYMAgGapqAg8ILTfWO6CqoW2gL0pqKd05Eei0PT589QjfQsfm0KNQdEONd2Jqs9d9qfReu4CGSs0++T51vZuccthtXqExb39V0ikUguFVbsVXB4eBiAqakp1q5d2/n+1NQU11xzTeeY6enpef/O8zxmZ2c7/354eJipqflN7O2vz3dM+/WFSCQSJBLdm7euBnat72VTf5qD0xXSpjavfC4IwgzN5UNZdq3vXfTY7XKcfRMlMon5qnntcpydo/nI5Thxjh/nurTHH8wmeOpEmYSukjA0NEXFF4Jq02WmFnDVSC7S+Ndu7CWT0Kk2PRK6eta61J1QxfDajdHm3i4rbLoBXhBQqLtUmx66qrImm0BX1a7KCtsS5umExk9s6UNTVfwgoGJ7XUuYt8f/9P1jzNYc1uYtUmaSuuOxb6LERKnBO27YFGn83/rJy/ncA0fxRSgRPzep0U6+aUp4XBQ29adJmjq262PpKoFoZ4LC8jzHC0iZOpv604seezhnoakKnhOqEya0tsRH2C/p+oKUoTCcixZM/s+ffzG7/vt3Lui4xdKXTqCpzAsiO0ryrf/X1PC4KLx6xyD/695naAtAzo2F2wGapoTHRWU1+oTFfX2XSCSSS4UVW7K4efNmhoeHuffeezvfK5fLPPjgg+zevRuA3bt3UywWeeSRRzrHfOc73yEIAq677rrOMd///vdx3dNlNN/61re4/PLL6e3t7Rwz9+e0j2n/nBc6uq7y9hs2kbUMjhYa80pmjhYa5CyD267fFEmBLu5ynDjHj3Nd2nPf2J9CVRRcX+AHAiHCz64fZso29KUizX1Df5obtw+gqgrFukvTC1rCGAHFuouqKty4bQ0bIty4t+feLivMJw12jua4dmMvO0dz5JPdlRXOFQq4bCjLSE+KoZzFSE+Ky4ayK1oIJpM2uXXn6QdMgTj90ebWnWvJRMyq5pMmlw1lUBSFUzWHYt2hVHcp1h1O1RxURWH7UIZ8cvHj112fpBEG734r8tCUcG/7fjtzq1I/l9TgeejJWKzJPP+81mRMejKLD/jWZBMYmtoJxFTl9Ef7e4YWPiyIQm8yMS8zKOZ8dI5JGfQmu3uI1/YJ2zGcY33E9/7FZDWXW0okEsnFZFkDsmq1ymOPPcZjjz0GhEIejz32GEePHkVRFN7//vfzp3/6p/zbv/0bTzzxBG9729sYGRnpeJVdccUVvPa1r+WXf/mX+eEPf8j999/Pe9/7Xt7ylrcwMjICwC/+4i9imibvete7ePLJJ/nyl7/MX/3VX80rN3zf+97HN7/5TT72sY+xf/9+/uiP/oiHH36Y9773vRd7SVYsN10xxIdu3cFlg1kqtsd4oUHF9rh8KMsHb93RlWdVuxzn6pE8xbrL2KkaxbrLztF85EzExRo/znUJG90Vdm/toz9t4ngBZdvD8QL6Mya7t/YBSqSGeFVVuOM127h2Y18no1Kqu9hu2O/xso19/OprtnZ1o9Re952jPfgBVGwPP4AXrevpat1XsxAMwN/84i5e/6K1nCm4pynw+het5W9+cVekcSHMSFyxNoelK2hK26xZELTGT+gKV6zNRcpIVO3Q+2o4lyBlani+wG6J2KQSGsO5BKqqUrWj9QONFxu8Yvsa8ufoK8xZOq/YvibSug9nLdIJHV0L5e4FoaeyIPxa08K+x+FstOyeAgzmLHKWvuB5zVkaQznrnIIolzJxX98lEonkUmBZSxYffvhhXvOa13S+bgdJt912G5/5zGf4nd/5HWq1Gu9+97spFovceOONfPOb38SyTv/R/MIXvsB73/tebrrppo4x9F//9V93Xs/n89xzzz3ccccdvPSlL2VgYIA/+IM/mOdVdv311/PFL36R3//93+d3f/d32b59O1/96le5+uqrL8IqrB5uumKIV2wd4J79k0yWmgznE+zZMYwZwez0TLYNZll3fZIvP3qU8YLNaK/Fm3dtwFoCL6n2+HGV+8RhIAynG+J3DOe5YjjHiZJN3fVJGRpr8xYBMHaqFrkhfttglg+//gq+/tg4dz85Rdn2yFk6t1w1xOuvGV2SG6Vtg1k2vTK9pGtzWiggSRAEZ61L0tSYKttLIAQTz/gQBmXFis2H/vWJzn7/6Bt20hMxIJiHgKSpk7MMfCHwhUBTFDRFwQ1E5KAgk9BJGhoNxyOT0PGEix+EaoUZUwcBqYRGJhHtPVtzPE5Vm6zrS9HTcDqiNu0+yUzS5FS1GWndbT9gY3+Kw9MBjheQNMIeSiHA9QMSusaGvjR2RLuBuuszkEmgKFCzXVxf4AmBroQWGGnLoD+diJw9bBMEYlWVLLZZjeWWEolEcjFZ1oDs1a9+9fM2lyuKwkc+8hE+8pGPnPOYvr4+vvjFLz7vz3nRi17Efffd97zHvOlNb+JNb3rT80/4Bc5CIgfPnWp0JXLQ5vN7x/jkfUc4WbE7N5D/8IPnuP0Vm3nr7k1LMv92uU8ctA2El5IzG+JHe+fPvWa7XTfE731mhn/50ThTlSZ+IDhVU/iXH43Tn7ViE8Z46Eihqz3TXpf9kyUOTFYpNVz8IOxryicNLh/OkLPMroVg4hofQvPmuYIkhbrLr335x7z9hk1dZ1WLDZfLhzPnnHuh7jJebCz6vZC1DPozJj8+VsduNWOF/VeCSbeJpaus60stKN5wISQNjVNVh1rTYzBn0ZtOdK4FhqYwXXEQLfXIxZI2dTb0pelNmRyYrFBsuHh+uC4D2QSXD2XJWkZXe2Ygk2AgYzJZajJbd/CDAE1V6UubDOcSgNLVnolDZOZiEuf1VyKRSFY7K1bUQ7KyiEvkAMJg7M67D9BsySMndIWmJ5gsN7jz7tCPaamCstVE3A3xn987xp9/8wANxwv7aJSwF2i8aPPn3+x+3ePaM6M9SRCCvc+EHmmmrmK2FP5maw57n5nltVcNdSUEM3f8pKlhqGF2aSnGv/fpKT56134qtkt/2iRpajQcn4PTFT56136AyEFZO8s0U3MwNYXR3iSqEopuOK7PiVITxxORskxrcxalhovtBQhxhjCGANsLKNkuayOKeoRjCVw/zEo23GCOqqhKIAQK5/ZBez7mvpf+84tHmKzYNByfpKkxnLV45lStKy+vueO/dGMP1aaP4weYmkomoXH4ZK2r92qc11+JRCKRLD8rVtRDsnKIU+TAcXw+ed8Rmp5PX8ogZWpoqkrK1OhLGTQ9n0/94AiO012pz2okzoZ4x/H5+HcPU3O8Ti9N0PosRHhj/4nvHo687nHumSAQPDdbxwsCPD+g4fhUmz4Nx8fzQ1XHsS48w9rjB0J0PLe81li6GvZkRR3f8wI+c/8YFdtlQ2+SrGWgqypZy2BDb5KK7fLZB8bwvGilc+0sU9X26M8kyFkGmURYvtifSVC1PU5VnUhZpuPFOidKdssAWiFhqFiGSsIIA2IFmCzaHC/WI8297vqkzDAjXKi7oe1CS76/UHepOz5JU49U9jf3vfTMqRo5y2BTy7fumVO1JRUPOnyyhqJAT8pAUeDwye7Gj/O9JJFIJJKVgQzIJOclTpGDe/ZPcrJikzL1ebLxAKqqkjJ1pss29+w/t0n3SmCpDYTbxNUQ/82nJ5kqNzsycGeZ2AqYLDf55tPR1j3OPfPosQLjxUYo168qrV8hNP1VVIWEpjJeaPDosUKkuT96rMB0pcmajEkgoFR3KNQcSnWHQIRKf9PlZqTxHz1WYGymRn/aXHC/96dNjpyqRZ57O8uknNMNK3wtStjx0FgB2w3tEMxWpNre5qYemnw3XJ+HxqLNPWVo1B2fVEInnwyFZootoZmepE7KDPvXUhGCSVi94kFxi8xIJBKJZPmRJYuS8zJX5GAhuhE5mCw18YUgoS98i5jQFeqOYLLUXPTYF4u4ezviaIg/MFnGF6cDMH/O/fvc7x2YLMOLRxc9fpx75mS1GXqaKQp9KR0/OO21palQb/pUmx4nq9H2zEzNCbNtQRCKYChKx2TZDQRlO/RTm4lgItwWqkieQwgnaWrM1pxIY8NpcYkZhQUNuTOWHllcwnZ9hABTU9FNNbRh6Ky7gusHNN0AO6JwRbgFFWzXp9pwced4hjmuTyZpPG+oeSHELS4Rx/hxvpckEolEsjKQAZnkvJwpLnEmDcePLC4xnE+gKWHPWGoBC6KmFzb1D+dXpgn3xertWOqGeNGqiFvo5nauf5KIVjkX654RQhAEAqXliaVrMNeKV1EVAjd4XsGg56MvZdBwfRwvQFNDQYm2BbIfQK3pk9AFfanFi1f0p00MTaXh+GStswsUGo7fURWMwkLiErVmKFc/mLO6EpfYPpTB1FUark9WU9G10zlVIcKAzdRVtg9lIs09XHOPYt0lOKNHzQmgWHc756Yb4haXWOrx43wvSSQSiWRlIEsWJeel3bB+omSfdZPbFpeI2hC/Z8cwa7IWdccjCObf/QdBQN0JFdf27Bju6neIg9Xc23HN+nzn/wWhoEf7Q5zjuMUQ557Z1J8maeo4XnDW2gaBwPECUqbOpoim1gPZRBh8CYGmgKooKIqCqoTeXr4IyyMHIpgI71rfy6b+NDM1Z8H9PlNz2DyQZtf63khzb697ww146cYedm/p5+Wb+9m9pZ+Xbuih4QaR1/3aDX1sH8zgBYJ606PphhLyTTeg3vTwAsFlQxmu3dAXae6mpjBRsjtlkGeaKwcCTpRszDONvi5x4nwvSSQSiWRlIAMyyXmJU1zCNDVuf8VmErrGbKtx3w8C6o7PbN3F0jXedePmJfE6W2pWc29HPmVizfECE+L0RxtLV8kvlLa8AOLcM/mkyWVDGQxNoWx7NFuBWbNlnK1rCtuHMuST0eZ+bLaBpasYqoLjC7xAIEQo7OH4AkNVSOgqx2YXf151XeXtN2wiaxkcLTTmrcvRQoOcZXDb9Zsi+7TFKS6h6yq/+ppt9KRMaq5PsRH21hUbDjXXpydl8p5Xb4s8930TZWz3+VOyDTdg30Q50virlTjfSxKJRCJZGcgaB8kF0W5Yb/dKTZVtErrGztE8e67qrleqLa3e9iGrO2GZ4tp8knfduHQ+ZEvN3N4OIQQV2+tIXWctfUl7O5baEDZrGQznLSaKDVxfzMuKKYChKQznrcieUnB6z3xz3yRPjJdCwQZT40WjPV311432JLlx2xocP2C6ZFOou9RaflV9KYPBvMUrtq/pKmOQNDRySZ2ZqkPD9WkKUJVQeKIvY+L60bOebUn7tg/ZbM3B0FQuH8py2/Xd+ZDBnHV/orXurkfK0HnRujy3XD3c1Xt1Y3+Ky4YyNF2fhut3ZOlThsZlQxk29kcv1TtRbHC+ZHIgwuNeaMR5/ZVIJBLJ8iMDskuMpb5xn0ucDfFv3b2JN790Pffsn2Sy1GQ4n2DPjuEVmRlr0+7tmGjJgU+Xm7h+gKGpDOYSrM1bS9LbcXi60rm5rrkeaUNn52ie1+6MfnOdtQy2DWZw/YCZahPHD7NAihKWjvWnE2xrlWF2ixCChuNTa7ooQBC1Ma1FO2Pw9GSZYs0hndBwgwBDVTF1lbX5ZFcZgy0DafIpgxMlm6br01agD1p9UqWGx0jeYstAtJJICIOyV21fw6PHCszUHPrTJrvW90bOLi3I3CYsZeF+wcXQLtENBGwfTHOi1KTpByQ0lbX5BIGAe56cYstAJtLaN9wLe3BxocddasQtSCKRSCSS5UMGZJcQcav9QbwN8aap8foXLV7Rb7kY7UnSkzT4//ZN4vg+YUtQqAtXaDgcOVXndTuHu8rUHJ6u8JffPsTBqQr+nPTBkZka+6cqvP/m7ZHNlTf0pdg3XiJpaMyNGdt9Uhv6Uksz98kKvgi7gUoNj8kf2xyYqkaee5uK7VKsu9Q7mZoALxBUbDfymADrelPkkgZPn6icFcQ4Abh1lx3DWdb1dvc+0HWVl2/u72qMhZgrNDPakyRl6tQdjycnypwo2ZGFZsaLDX50rMDJio3nC/oyZkfBcabmoqkejx4NLQmiXCO2DFyYGMiFHncpErcgiUQikUiWB9lDdonQvgnbN1GiJ2WwZSBDT8pg30SJT98/xuHpynJP8ZKk0HCoNF1sx0fXFJKmhq4p2I5PpelSqEcPDoJA8MX/OMqPjxXxA0HWMuhLm2QtAz8Q/PhYkS89eDS6aIgAQ1PpSydY15NkfV+SdT1J+tIJDE2N5FU1b+4PtucekLV0+tIJspaOHwT8+FiRL0ace3tdnpwoU3c8XC/A8wSuF4pLPDlR7mpdPC/gmemzg7E2gvD9FtW8OU7mCs1sW5NGCCjUHYSAbWvSXQnNVGyXozN1XC+gL22S0DVURSGha/SlTTw/4NhsPXJA3HeBypIXepxEIpFIJKsFGZBdAqxmtb/VzPFCnQOTFfJJg960ie8Lak0f3xf0pU3yls6ByTLHC/VI4x8r1PmPI7OoikJ/2iShq60b4FAWXVUU9j47y7EI448XGxQbLi/b1MtgziKAUBwDGMpbvGxTL4W6G1mQ5Hihzn88O4OmQH8mMe/mvT+TQFXgwWdnIq3NsUKdbz09Sanu4voCQ1dJmhqGruL6gmLd5Z6npiKtC8DdT09SqLvoCpiq0lJaDDOHpqqgK6EE+90RTbPjpC00kzRUHn6uyN5nZ3jw2Rn2PjvDw88VSRpqZKGZatOj4fokDG1BEZtEy9i52oxWUnhw6sIeGl3ocRKJRCKRrBZkQHYJsJrV/uYSBIJjs3X2T5Y5Nltf8QHks6dqlOou2YQWZpPm9OsAZCydYsPl2VO1SOMfOVWj2HDoafldNV2fuuPRbPkw5VMGpYbDkQjjtwVJRnpSXLuxh6tHclw2lOXqkRwv3dDD2p4kTc+PLEjSXptcylhwT+ZTRuS1OTxdYarcRAiBZWjoamjcrKsKlqGBEEyV7chZ4f2TFYIgFDYxdQXLULF0FctQMfXQl8wPwuNWGjXH41S1yYGpKicrNpah0Zs2sQyNk5WwVPRUtRnpvGZaQjXNBTzehBA03YCUqZGxolXCX6j5+0o2iZdIJBKJJAqyh+wSYK7a30IspdpfXFyM/rc4cIOAkxUfAZi6iqYo+EJQc3zqrTLGblAE2K7HTNUPs28tNcF0QiOViC54MleQpG0g7AUBuqoyUbQZzie6FiQRCijnLHyMvi6HT1bxglB+/oxYD0UBTVVwA8Hhk1VuumLx4+csoyOCoSjK/GAbCAhdi3NLIHiy1CQNjVPV0Ax6KJfoBMMJXcFMm61ANjxusWQTBhv6UhybrTNbc8hYeqeHrGp76LrK+t4k2US0dRnttcJsJODDPMVFVQENCFrHSSQSiURyKSEzZJcA7Zvr+jkCrobjL4naH8STxVqt/W+b+lOIlvJeQlNACLwgACFIaAqNViZrU0Qp8C0DaSxD4+hsg1M1h7rr0/R86q7PqZrDsdkGSUOLpPY32pOkJ2Xw0FiBqXIDy1DpTZlYhspUucFDYwV6UkZkUY/NA2l6kibFurtgNqVUd8knTTZHmHvS0EIDayHO6vMSrfEVJVrQAXDzlYNYhobjiwWNp11fkDQ0br5yMNL4cRKGXwIFgRCCcsNlttak3Gifh/C1KOHwaE+Sl6zvZTBrsSabwHYDCnUH2w1Yk00wmEmwa0Nv5D3z5l0byCQMPMDSIGmoWLoSftbAI1QHffOuDZHGl0gkEolkpSIzZJcAoz1Jtq7JsG+iRCahzysRE0JwomSzczTflWIexJPFOlOEoNr0KdQdTE1l25o0h0/WupLSjhNFUchZBrWmT9H2Qtl4BIIwc6OikE2cXbJ3oYzkkyQMFaclHmHqKpqq4gdizvc0RvIRz2s71lgozRTxpr3N+t4UP7G5j289PcVMzSE7J5tSsT0CIdi9pY/1EZQKLxvKkjTC0jnXC9A1tRWggecHCMKb+MuGou3Jzf0Zrt/Sx3cPnsL2AnRNQVcUPCHw/NB36/qtfWzuX3lqf3XXZyCTYMz2eGKiHCpztvwMNFVhTSZBfyZBvfWwYDG07QYmSg1mqk3W9SbRVAU/CD34+jOJruwGLEvnbddv5BPfe4aGLzBVgaYS7vcADFXhrbs3YkUsiZRIJBKJZKUi/7JdAsy9UTo0HfaSJU2NhuNzomTTlza7ulGC+VLaa/MWKTNJ3fHYN1FiotToSkq7LULwyHPFeaVzfSmT4Xyi0/+20uSeG65Pb9rgZLVJww1Qacc4Al+Aaaj0po1OpmyxTJQaNFsiCkIIAiEIvLBcztTDIMRxPSZKDTb0Ly7TNFfU40SpSaHuUG166KrKUM5iOJfoiHpEWXdVVfjFn9jAdLXJwakKFft09lZTFV68vodfuG5DpD157YY+Lh/Ksm+ijEI7KwkoYSypKgo7hrNcu6Fv0WO35/7B/3QFxcbjPDlRxvEDPHF63a8ayfGBW69YcQ8IIMyWu37AbN3FD0RYAtEKuP1AUKi7rPODyNnyMw2K645HQtd40bqeJTEo/q09lwPwuQeeo9p0cfywXDFvGbx198bO6xKJRCKRXErIgOwS4cwbpamyTULX2Dma7/pGKc4sVluEYKbWpNH0UNSwitb1AyZLdUq2Q386sST9b47jL6nxdNLQqDsBmYROJhH+f+iHpZA2VQQKdSeIXDr37KkathuwrteianuUG16nhyyf1ElbOrWmz7OnaosOyNp9h1sGMoz2JDlRsqm7PilDY20+VF0cO1Xrat23DWZ5/83buevxEzw0VqDquGRMg5dv7uW1O9dG3pO6rvKrr9nGH3/tKWaqNtCJxwAYyFi859XbujJZ3jaY5X+88UV8/UfHufupacq2S84yeO1Vg7zumnUrtq9xKJNgomjj+j4DaYNAdHK2qIpgtu5yomQzlElE/hlxGxT/1p7LueOVW/nyo0cZL9iM9lq8edcGmRmTSCQSySWL/At3CRHXjdKZUtqFuoPnh6VivSmTtV1ksVKGxqlqk5MVm6YbYHtBu8IKS1dJND0Q4XHd8Pm9Y3zyviOcrNidoObO7EFuf8Vm3rp7U6Qx2/06pqYwmEvieEFnbFNXmSrbkft12ggFHE9Qabg0W2vjKVBuCHR9aUQ92hmy9jkdL9qsXQJRjzaKqpBMaAhFkDS1s0skI3DTFUNMFBv8/fefZXrOOR3KWdz+is3cdMVQ1z/juZk6Dx8rUbRdHC8gsF0eOlri6vV9KzYge2y8SNPzSRoaticwdQVdUfGFwPYESUPHdn0eGy92ZUodt0GxZencdv2W2MaXSCQSiWQlIQOyS4w4bpROZ7Ecmq5PxjIwLB3XF5ys2JRtl/60GSmbIoBKw6NQ9zrS5aoSKqw1vIC6G2Dp3jlNei+Ez+8d4867D9D0fFKmTkJXaHqCyXKDO+8+ABApKGv368wodFTnLF0LS8ZaX/eno/XrQCiMoaFwvNAI10ZTO2tj+4LxQoO1OSuSMMZoT5KepMG3np7C1FWyc87pdMXmeKHOniuHuuo7nFvmOtqTJGXq1J3QuPlEyY5c5toee/9khSvX5rh6XR4RCBRVIfAF+ycrHJ6udBU03fv0FB+9az+V1t5ulwAfmq7y0bv2AyxJ0LfUzNQcAEZ6kpQboW+YI4Iwa5vQyVk6szWnc5xEIpFIJJLlRwZkkvMSp5R2pelSaYYBl4pAVdSWIAYoBAQoVJoelaYbae6O4/PJ+47Q9Hz6UgZqqyQyZYKlK8zWXT71gyO8+aXrF12+mDZ1BjIJBjJmRzq+1vTQVJXBVh8WKJGzTGuzFr4IyyB1hbPWxhcQiIC12Ygy4O1EVUt9PIpn1wAAFixJREFUL/xGSwQCugqCzzQrb++ZrGWQSegcmq5GLnOdO/Zlw9mzRGy6GRvA8wI+c/8YFdtlQ2+ys2eylkra1DhaaPDZB8Z41fY1XZVFxkF/2sTQwjmN9FhnZW2rTQ9DC43FJRKJRCKRrAxW1t2EZEUyV0p7YaJLaY+dquF4PhlTJaHrBC0lu0AIEoZOxlRxPJ+xiObK9+yf5GTFJmXqnRvrNqqqkjJ1pss29+yfXPTYbXXLhhvw0o097N7Sz8s397N7Sz8v3dBDww3YNpiJnGV6bLxIICCd0FBb6oqeL0KxBjUMDnwRHrdYxosNivVQ1GMol8R2A4otCfOhfJKXbeql2BL1iEKcZuVxG6E/eqzA2EyN/rS54J7pT5scOVXj0WOFSOPHya71vWzqTzNTcxBCkDC0MCvcEoaZqTlsHkiza33vck9VIpFIJBJJC5khk5yXhUrz5hrCdlOaF4oNhOa7WUvHD0RHhEBTFepNF1VVnsdg+PmZLDXxhSChL/zvE7pC3RFMlpqLHnuuuuXhkzXW5i16UgYNx+fwyVrX6pbtsrL1vSnKDfcsY+hc0ohcfjZX1GNdb4qK7eH4AaamhudBiK5EPeI0K4/bCH2m5uD6Qdjvdo7xV2rZn66rvP2GTXz0rv0cLTTmlVvO1BxylsFt129acZk9iUQikUheyMiATHJe4izNW5NNkLFCoYGG62PqakeEoOH6oChkTI012WiqcMP5BJoS9oylFqjSanphgDOcjzZ+nOqW88vPzhYN6ab8bK6ZeNYyyCWNea83ml5Xoh5njn8m3ZiVxzk2nF73huOTtc4OXBqOv6LL/tq9bZ+5f4yxmRqzNQdDU7l8KMtt129akb1vEolEIpG8kJEBmeS8zDWefunGHqpNv5NNySQ0Dp+sRTae3rW+l+2DWZ46UcbSFWxP4IoARVFIGSq2J7hsKBu5xGrPjmHuzB5kstzA0pV5JWhBEFB3PNbmk+zZMRxpfIhP3bJdfnZwukLa1EjM6dELgoCZmsPlEdcmbjPxOMePe+5nrvuZe6abdb9Y3HTFEK/avoZHjxWYqTn0p012re+VmTGJRCKRSFYg8q+z5Ly0S/P60iaHT9ZQFOhJGSgKXZfmtUusetMmXgB9aYOhvEVf2mh9bXZVYmWaGre/YjMJXWO27lJ3fPwgoO74zNZdLF3jXTdu7sqPDE6rW+4YzrG+L7UknkzttclaBkcLDSq2ixcEVGyXo4VGV+Vnc8/poenqvLEPTVe7LreMc/y45x7nul9MdF3l5Zv7ufXqtbx8c/+Kn69EIpFIJC9UFCFEN2Jqkhblcpl8Pk+pVCKXyy33dGLh8HSlU5rX9MKysG2Dma5L8yCUGW+XWLl+gKGpbB5IL1mJ1UI+ZIM5i3fdGN2H7GIR59rEeU7jHj/uuce9JyUSiUQikVy6LCY2kAHZEvFCCMgglBxf6tK8Np4XxFpi5Tg+9+yfZLLUZDifYM+O4a4zYxeLONcmznMa9/hxzz3uPSmRSCQSieTSRAZky8ALJSCTSCQSiUQikUgkz89iYgP5qFcikUgkEolEIpFIlgkZkEkkEolEIpFIJBLJMiEDMolEIpFIJBKJRCJZJmRAJpFIJBKJRCKRSCTLhAzIJBKJRCKRSCQSiWSZkAGZRCKRSCQSiUQikSwTMiCTSCQSiUQikUgkkmVCBmQSiUQikUgkEolEskzIgEwikUgkEolEIpFIlgkZkEkkEolEIpFIJBLJMiEDMolEIpFIJBKJRCJZJmRAJpFIJBKJRCKRSCTLhAzIJBKJRCKRSCQSiWSZ0Jd7ApcKQggAyuXyMs9EIpFIJBKJRCKRLCftmKAdIzwfMiBbIiqVCgDr169f5plIJBKJRCKRSCSSlUClUiGfzz/vMYq4kLBNcl6CIGBiYoJsNouiKMs9Hck5KJfLrF+/nmPHjpHL5ZZ7OpIlQJ7TSxN5Xi895Dm9NJHn9dJDntOlQQhBpVJhZGQEVX3+LjGZIVsiVFVl3bp1yz0NyQWSy+XkReYSQ57TSxN5Xi895Dm9NJHn9dJDntPuOV9mrI0U9ZBIJBKJRCKRSCSSZUIGZBKJRCKRSCQSiUSyTMiATPKCIpFI8Id/+IckEonlnopkiZDn9NJEntdLD3lOL03keb30kOf04iNFPSQSiUQikUgkEolkmZAZMolEIpFIJBKJRCJZJmRAJpFIJBKJRCKRSCTLhAzIJBKJRCKRSCQSiWSZkAGZRCKRSCQSiUQikSwTMiCTXJKMj4/zX//rf6W/v59kMsnOnTt5+OGHO6+//e1vR1GUeR+vfe1rl3HGkvOxadOms86ZoijccccdANi2zR133EF/fz+ZTIY3vvGNTE1NLfOsJc/H+c7pq1/96rNe+5Vf+ZVlnrXk+fB9nw9/+MNs3ryZZDLJ1q1b+ZM/+RPm6ocJIfiDP/gD1q5dSzKZ5Oabb+bQoUPLOGvJ+biQ8yr/rq4+KpUK73//+9m4cSPJZJLrr7+ehx56qPO6fK9ePPTlnoBEstQUCgVuuOEGXvOa13DXXXexZs0aDh06RG9v77zjXvva1/LpT3+687WUd13ZPPTQQ/i+3/l63759/NRP/RRvetObAPiN3/gNvvGNb/CVr3yFfD7Pe9/7Xn7u536O+++/f7mmLDkP5zunAL/8y7/MRz7ykc7XqVTqos5Rsjj+/M//nI9//ON89rOf5aqrruLhhx/mHe94B/l8nl//9V8H4C/+4i/467/+az772c+yefNmPvzhD3PLLbfw1FNPYVnWMv8GkoW4kPMK8u/qauP2229n3759fP7zn2dkZIR//Md/5Oabb+app55idHRUvlcvJkIiucT4wAc+IG688cbnPea2224Tb3jDGy7OhCSx8L73vU9s3bpVBEEgisWiMAxDfOUrX+m8/vTTTwtA7N27dxlnKVkMc8+pEEK86lWvEu973/uWd1KSRfG6171OvPOd75z3vZ/7uZ8Tv/RLvySEECIIAjE8PCzuvPPOzuvFYlEkEgnxpS996aLOVXLhnO+8CiH/rq426vW60DRNfP3rX5/3/V27donf+73fk+/Vi4wsWZRccvzbv/0b1157LW9605sYHBzkJS95CX//939/1nHf/e53GRwc5PLLL+c973kPMzMzyzBbSRQcx+Ef//Efeec734miKDzyyCO4rsvNN9/cOWbHjh1s2LCBvXv3LuNMJRfKmee0zRe+8AUGBga4+uqr+dCHPkS9Xl/GWUrOx/XXX8+9997LwYMHAfjxj3/MD37wA2699VYAjhw5wuTk5Lz3aj6f57rrrpPv1RXM+c5rG/l3dfXgeR6+75+V6Uomk/zgBz+Q79WLjCxZlFxyPPvss3z84x/nN3/zN/nd3/1dHnroIX79138d0zS57bbbgLCs4ud+7ufYvHkzzzzzDL/7u7/Lrbfeyt69e9E0bZl/A8n5+OpXv0qxWOTtb387AJOTk5imSU9Pz7zjhoaGmJycvPgTlCyaM88pwC/+4i+yceNGRkZGePzxx/nABz7AgQMH+Jd/+Zflm6jkefngBz9IuVxmx44daJqG7/v82Z/9Gb/0S78E0Hk/Dg0Nzft38r26sjnfeQX5d3W1kc1m2b17N3/yJ3/CFVdcwdDQEF/60pfYu3cv27Ztk+/Vi4wMyCSXHEEQcO211/Lf//t/B+AlL3kJ+/bt4xOf+EQnIHvLW97SOX7nzp286EUvYuvWrXz3u9/lpptuWpZ5Sy6cT33qU9x6662MjIws91QkS8RC5/Td73535/937tzJ2rVruemmm3jmmWfYunXrckxTch7+6Z/+iS984Qt88Ytf5KqrruKxxx7j/e9/PyMjI53rr2T1cSHnVf5dXX18/vOf553vfCejo6NomsauXbv4hV/4BR555JHlntoLDlmyKLnkWLt2LVdeeeW8711xxRUcPXr0nP9my5YtDAwMcPjw4binJ+mS5557jm9/+9vcfvvtne8NDw/jOA7FYnHesVNTUwwPD1/kGUoWy0LndCGuu+46APk+XcH89m//Nh/84Ad5y1vews6dO3nrW9/Kb/zGb/DRj34UoPN+PFMBVb5XVzbnO68LIf+urny2bt3K9773ParVKseOHeOHP/whruuyZcsW+V69yMiATHLJccMNN3DgwIF53zt48CAbN2485785fvw4MzMzrF27Nu7pSbrk05/+NIODg7zuda/rfO+lL30phmFw7733dr534MABjh49yu7du5djmpJFsNA5XYjHHnsMQL5PVzD1eh1VnX9roWkaQRAAsHnzZoaHh+e9V8vlMg8++KB8r65gzndeF0L+XV09pNNp1q5dS6FQ4O677+YNb3iDfK9ebJZbVUQiWWp++MMfCl3XxZ/92Z+JQ4cOiS984QsilUqJf/zHfxRCCFGpVMR/+2//Tezdu1ccOXJEfPvb3xa7du0S27dvF7ZtL/PsJc+H7/tiw4YN4gMf+MBZr/3Kr/yK2LBhg/jOd74jHn74YbF7926xe/fuZZilZDGc65wePnxYfOQjHxEPP/ywOHLkiPjXf/1XsWXLFvHKV75ymWYquRBuu+02MTo6Kr7+9a+LI0eOiH/5l38RAwMD4nd+53c6x/yP//E/RE9Pj/jXf/1X8fjjj4s3vOENYvPmzaLRaCzjzCXPx/nOq/y7ujr55je/Ke666y7x7LPPinvuuUe8+MUvFtddd51wHEcIId+rFxMZkEkuSb72ta+Jq6++WiQSCbFjxw7xd3/3d53X6vW62LNnj1izZo0wDENs3LhR/PIv/7KYnJxcxhlLLoS7775bAOLAgQNnvdZoNMSv/uqvit7eXpFKpcTP/uzPihMnTizDLCWL4Vzn9OjRo+KVr3yl6OvrE4lEQmzbtk389m//tiiVSss0U8mFUC6Xxfve9z6xYcMGYVmW2LJli/i93/s90Ww2O8cEQSA+/OEPi6GhIZFIJMRNN9204HtasnI433mVf1dXJ1/+8pfFli1bhGmaYnh4WNxxxx2iWCx2Xpfv1YuHIsQcm3WJRCKRSCQSiUQikVw0ZA+ZRCKRSCQSiUQikSwTMiCTSCQSiUQikUgkkmVCBmQSiUQikUgkEolEskzIgEwikUgkEolEIpFIlgkZkEkkEolEIpFIJBLJMiEDMolEIpFIJBKJRCJZJmRAJpFIJBKJRCKRSCTLhAzIJBKJRCKRSCQSiWSZkAGZRCKRSCQSiUQikSwTMiCTSCQSyarm5MmTvOc972HDhg0kEgmGh4e55ZZbuP/++5d7ahKJRCKRnBd9uScgkUgkEkk3vPGNb8RxHD772c+yZcsWpqamuPfee5mZmVnuqV10HMfBNM3lnoZEIpFIFoHMkEkkEolk1VIsFrnvvvv48z//c17zmtewceNGXv7yl/OhD32I//yf/zMAiqLw8Y9/nFtvvZVkMsmWLVv453/+53njHDt2jP/yX/4LPT099PX18YY3vIGxsbF5x/zDP/wDV111FYlEgrVr1/Le9773vPMTQvBHf/RHnezdyMgIv/7rv955vdls8oEPfID169eTSCTYtm0bn/rUpzqvf+973+PlL39552d+8IMfxPO8zuuvfvWree9738v73/9+BgYGuOWWWwDYt28ft956K///du4vpMkvjAP4d0Xh6l1/zAo12wipNEY4CVldCIo2AjGyIpGyNKMmdSGFtJIVddEfZLAI88IwUowsXAaRWDiToVRErxprreWFJRgZgYucMk8XP3hpPy3RsrH4fuC92Dnn2XnOe/e853AkScLKlSuxd+9efPr0adrvl4iIZh8LMiIiiliSJEGSJDgcDgQCgZ+Oq6ioQF5eHmRZRkFBAfbs2QO32w0AGBsbw9atW6HRaNDR0QGXywVJkmAymTA6OgoAqKqqQmlpKQ4dOoSenh40NzcjMTFxyvzu3r0Lm82G6upqeL1eOBwO6PV6pX/fvn1oaGiA3W6H2+1GdXU1JEkCAHz48AHbtm3Dpk2bIMsyqqqqUFNTg/Pnz4fMcePGDcyfPx8ulwvXrl3Dly9fkJGRgZSUFDx//hwPHz7E4OAgdu/ePe33S0REf4EgIiKKYHfu3BFLly4VUVFRYvPmzeLkyZNClmWlH4A4fPhwSExaWpo4cuSIEEKImzdvinXr1onx8XGlPxAICLVaLVpaWoQQQsTFxYlTp05NO7fKykqxdu1aMTo6OqHP4/EIAKK1tXXSWIvFMiGvq1evCkmSRDAYFEIIkZ6eLlJSUkLizp07J7Kzs0Pa+vv7BQDh8XimvQYiIppd3CEjIqKIlpeXh4GBATQ3N8NkMsHpdMJgMKC2tlYZYzQaQ2KMRqOyQybLMt6+fQuNRqPsuEVHR2NkZAQ+nw8fP37EwMAAMjMzp53brl278O3bN6xZswYlJSVoampSjhy+fPkSc+fORXp6+qSxbrcbRqMRKpVKaduyZQv8fj/ev3+vtKWmpobEybKMtrY2ZS2SJGH9+vUAAJ/PN+01EBHR7OKlHkREFPGioqKQlZWFrKwsVFRU4ODBg7Bardi/f/+UsX6/H6mpqaivr5/Qt3z5csyZM/NvlwkJCfB4PHj06BFaW1thNptx+fJltLe3Q61Wz/h/f7Rw4cKQ336/Hzk5Obh48eKEsbGxsX9kTiIi+nO4Q0ZERP+c5ORkfP36Vfnd1dUV0t/V1YWkpCQAgMFggNfrxYoVK5CYmBjyLF68GBqNBjqdDo8fP55RLmq1Gjk5ObDb7XA6nejs7ERPTw/0ej3Gx8fR3t4+aVxSUhI6OzshhFDaXC4XNBoNVq1a9dP5DAYDXr16BZ1ON2E9/y/eiIgo/FiQERFRxBoaGkJGRgbq6urQ3d2Nvr4+NDY24tKlS8jNzVXGNTY24vr163jz5g2sViuePn2q3JJYUFCAmJgY5ObmoqOjA319fXA6nTh27JhyNPDMmTOorKyE3W6H1+vFixcvcOXKlSnzq62tRU1NDXp7e/Hu3TvU1dVBrVZDq9VCp9OhsLAQRUVFcDgcyry3b98GAJjNZvT39+Po0aN4/fo17t27B6vVirKysl/u2pWWluLz58/Iz8/Hs2fP4PP50NLSggMHDiAYDP7O6yYiolnAI4tERBSxJElCWloabDYbfD4fxsbGkJCQgJKSElgsFmXc2bNncevWLZjNZsTGxqKhoQHJyckAgAULFuDJkycoLy/Hjh07MDw8jPj4eGRmZmLRokUAgMLCQoyMjMBms+H48eOIiYnBzp07p8xvyZIluHDhAsrKyhAMBqHX63H//n0sW7YMwH+3N1osFpjNZgwNDWH16tVK3vHx8Xjw4AFOnDiBjRs3Ijo6GsXFxTh9+vQv54yLi4PL5UJ5eTmys7MRCASg1WphMpl+6/glERHNDpX48SwEERHRP0alUqGpqQnbt28PdypEREQT8FMZERERERFRmLAgIyIimqH6+vqQ6+V/fDZs2BDu9IiIKALwyCIREdEMDQ8PY3BwcNK+efPmQavV/uWMiIgo0rAgIyIiIiIiChMeWSQiIiIiIgoTFmRERERERERhwoKMiIiIiIgoTFiQERERERERhQkLMiIiIiIiojBhQUZERERERBQmLMiIiIiIiIjC5DvwOO3aHH5bIQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Количество строк до удаления выбросов: 785\n",
      "Количество строк после удаления выбросов: 721\n"
     ]
    }
   ],
   "source": [
    "column1 = \"Spec_score\"\n",
    "column2 = \"Price\"\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.scatter(df[column1], df[column2], alpha=0.5)\n",
    "plt.xlabel(column1)\n",
    "plt.ylabel(column2)\n",
    "plt.title(f\"Scatter Plot of {column1} vs {column2} (Before Removing Outliers)\")\n",
    "plt.show()\n",
    "\n",
    "def remove_outliers(df, column):\n",
    "    Q1 = df[column].quantile(0.25)\n",
    "    Q3 = df[column].quantile(0.75)\n",
    "    IQR = Q3 - Q1\n",
    "    lower_bound = Q1 - 1.5 * IQR\n",
    "    upper_bound = Q3 + 1.5 * IQR\n",
    "    return df[(df[column] >= lower_bound) & (df[column] <= upper_bound)]\n",
    "\n",
    "df_cleaned = df.copy()\n",
    "for column in [column1, column2]:\n",
    "    df_cleaned = remove_outliers(df_cleaned, column)\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.scatter(df_cleaned[column1], df_cleaned[column2], alpha=0.5)\n",
    "plt.xlabel(column1)\n",
    "plt.ylabel(column2)\n",
    "plt.title(f\"Scatter Plot of {column1} vs {column2} (After Removing Outliers)\")\n",
    "plt.show()\n",
    "\n",
    "print(f\"Количество строк до удаления выбросов: {len(df)}\")\n",
    "print(f\"Количество строк после удаления выбросов: {len(df_cleaned)}\")\n",
    "\n",
    "df = df_cleaned"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Разбиение данных на выборки."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Размеры выборок:\n",
      "Обучающая выборка: 432 записей\n",
      "company\n",
      "Realme      86\n",
      "Samsung     70\n",
      "Motorola    50\n",
      "Vivo        48\n",
      "Xiaomi      45\n",
      "Poco        32\n",
      "OnePlus     15\n",
      "iQOO        14\n",
      "OPPO        12\n",
      "POCO        11\n",
      "Honor       11\n",
      "TCL         11\n",
      "Lava         9\n",
      "Oppo         5\n",
      "Huawei       5\n",
      "itel         3\n",
      "Google       2\n",
      "Gionee       1\n",
      "IQOO         1\n",
      "Lenovo       1\n",
      "Name: count, dtype: int64\n",
      "Контрольная выборка: 144 записей\n",
      "company\n",
      "Vivo        27\n",
      "Samsung     27\n",
      "Realme      21\n",
      "Xiaomi      12\n",
      "Poco        11\n",
      "Motorola    10\n",
      "OnePlus      7\n",
      "OPPO         6\n",
      "POCO         6\n",
      "Honor        3\n",
      "itel         3\n",
      "Lava         2\n",
      "LG           2\n",
      "iQOO         2\n",
      "Lenovo       2\n",
      "Oppo         1\n",
      "Itel         1\n",
      "Google       1\n",
      "Name: count, dtype: int64\n",
      "Тестовая выборка: 145 записей\n",
      "company\n",
      "Samsung     27\n",
      "Vivo        25\n",
      "Realme      16\n",
      "Xiaomi      12\n",
      "Motorola    11\n",
      "Poco        10\n",
      "OnePlus      7\n",
      "TCL          7\n",
      "iQOO         7\n",
      "Huawei       5\n",
      "Oppo         4\n",
      "Lenovo       2\n",
      "Honor        2\n",
      "Lava         2\n",
      "itel         2\n",
      "Tecno        1\n",
      "Google       1\n",
      "OPPO         1\n",
      "Coolpad      1\n",
      "POCO         1\n",
      "Itel         1\n",
      "Name: count, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "X = df\n",
    "y = df[\"company\"]\n",
    "\n",
    "train_df, X_temp, y_train, y_temp = train_test_split(\n",
    "    X, y, test_size=0.4, random_state=42\n",
    ")\n",
    "val_df, test_df, y_val, y_test = train_test_split(\n",
    "    X_temp, y_temp, test_size=0.5, random_state=42\n",
    ")\n",
    "\n",
    "print(\"Размеры выборок:\")\n",
    "print(f\"Обучающая выборка: {train_df.shape[0]} записей\")\n",
    "print(train_df.company.value_counts())\n",
    "print(f\"Контрольная выборка: {val_df.shape[0]} записей\")\n",
    "print(val_df.company.value_counts())\n",
    "print(f\"Тестовая выборка: {test_df.shape[0]} записей\")\n",
    "print(test_df.company.value_counts())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Oversampling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Размеры выборок:\n",
      "Обучающая выборка: 1720 записей\n",
      "company\n",
      "Vivo        86\n",
      "Motorola    86\n",
      "Oppo        86\n",
      "POCO        86\n",
      "iQOO        86\n",
      "Xiaomi      86\n",
      "Realme      86\n",
      "OnePlus     86\n",
      "Poco        86\n",
      "Samsung     86\n",
      "TCL         86\n",
      "Gionee      86\n",
      "Honor       86\n",
      "OPPO        86\n",
      "Lava        86\n",
      "itel        86\n",
      "Huawei      86\n",
      "Google      86\n",
      "IQOO        86\n",
      "Lenovo      86\n",
      "Name: count, dtype: int64\n",
      "Контрольная выборка: 486 записей\n",
      "company\n",
      "Vivo        27\n",
      "Honor       27\n",
      "Motorola    27\n",
      "POCO        27\n",
      "Samsung     27\n",
      "itel        27\n",
      "Lava        27\n",
      "Xiaomi      27\n",
      "Realme      27\n",
      "OnePlus     27\n",
      "Poco        27\n",
      "iQOO        27\n",
      "LG          27\n",
      "Oppo        27\n",
      "Itel        27\n",
      "OPPO        27\n",
      "Google      27\n",
      "Lenovo      27\n",
      "Name: count, dtype: int64\n",
      "Тестовая выборка: 567 записей\n",
      "company\n",
      "Oppo        27\n",
      "Huawei      27\n",
      "Samsung     27\n",
      "Motorola    27\n",
      "TCL         27\n",
      "Realme      27\n",
      "Xiaomi      27\n",
      "Poco        27\n",
      "Google      27\n",
      "Vivo        27\n",
      "iQOO        27\n",
      "Tecno       27\n",
      "OnePlus     27\n",
      "Honor       27\n",
      "OPPO        27\n",
      "Lenovo      27\n",
      "Lava        27\n",
      "itel        27\n",
      "Coolpad     27\n",
      "POCO        27\n",
      "Itel        27\n",
      "Name: count, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "def oversample(df):\n",
    "    X = df.drop(\"company\", axis=1)\n",
    "    y = df[\"company\"]\n",
    "\n",
    "    oversampler = RandomOverSampler(random_state=42)\n",
    "    X_resampled, y_resampled = oversampler.fit_resample(X, y) # type: ignore\n",
    "\n",
    "    resampled_df = pd.concat([X_resampled, y_resampled], axis=1)\n",
    "    return resampled_df\n",
    "\n",
    "train_df_overs = oversample(train_df)\n",
    "val_df_overs = oversample(val_df)\n",
    "test_df_overs = oversample(test_df)\n",
    "\n",
    "print(\"Размеры выборок:\")\n",
    "print(f\"Обучающая выборка: {train_df_overs.shape[0]} записей\")\n",
    "print(train_df_overs.company.value_counts())\n",
    "print(f\"Контрольная выборка: {val_df_overs.shape[0]} записей\")\n",
    "print(val_df_overs.company.value_counts())\n",
    "print(f\"Тестовая выборка: {test_df_overs.shape[0]} записей\")\n",
    "print(test_df_overs.company.value_counts())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Дискретизация числовых признаков"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Rating</th>\n",
       "      <th>Spec_score</th>\n",
       "      <th>No_of_sim</th>\n",
       "      <th>Ram</th>\n",
       "      <th>Battery</th>\n",
       "      <th>Display</th>\n",
       "      <th>Camera</th>\n",
       "      <th>External_Memory</th>\n",
       "      <th>Android_version</th>\n",
       "      <th>...</th>\n",
       "      <th>Inbuilt_memory</th>\n",
       "      <th>fast_charging</th>\n",
       "      <th>Screen_resolution</th>\n",
       "      <th>Processor</th>\n",
       "      <th>Processor_name</th>\n",
       "      <th>company</th>\n",
       "      <th>Spec_score_bin</th>\n",
       "      <th>Battery_bin</th>\n",
       "      <th>Ram_bin</th>\n",
       "      <th>Camera_bin</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Vivo Y21T</td>\n",
       "      <td>3.95</td>\n",
       "      <td>74</td>\n",
       "      <td>Dual Sim, 3G, 4G, VoLTE,</td>\n",
       "      <td>4</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>128 GB inbuilt</td>\n",
       "      <td>18W Fast Charging</td>\n",
       "      <td>1600 x 720 px</td>\n",
       "      <td>Octa Core</td>\n",
       "      <td>Snapdragon 680</td>\n",
       "      <td>Vivo</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Motorola Moto G23</td>\n",
       "      <td>4.40</td>\n",
       "      <td>77</td>\n",
       "      <td>Dual Sim, 3G, 4G, VoLTE,</td>\n",
       "      <td>4</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Memory Card Supported, upto 512 GB</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>128 GB inbuilt</td>\n",
       "      <td>30W Fast Charging</td>\n",
       "      <td>720 x 1600 px</td>\n",
       "      <td>Octa Core</td>\n",
       "      <td>Helio  G85</td>\n",
       "      <td>Motorola</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Oppo A78 4G</td>\n",
       "      <td>4.25</td>\n",
       "      <td>81</td>\n",
       "      <td>Dual Sim, 3G, 4G, VoLTE,</td>\n",
       "      <td>8</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>128 GB inbuilt</td>\n",
       "      <td>67W Fast Charging</td>\n",
       "      <td>1080 x 2400 px</td>\n",
       "      <td>Octa Core</td>\n",
       "      <td>Snapdragon 680</td>\n",
       "      <td>Oppo</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>POCO M4 Pro 4G (8GB RAM + 128GB)</td>\n",
       "      <td>4.45</td>\n",
       "      <td>81</td>\n",
       "      <td>Dual Sim, 3G, 4G, VoLTE,</td>\n",
       "      <td>8</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>64.0</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>128 GB inbuilt</td>\n",
       "      <td>33W Fast Charging</td>\n",
       "      <td>1080 x 2400 px</td>\n",
       "      <td>Octa Core</td>\n",
       "      <td>Helio G96</td>\n",
       "      <td>POCO</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>iQOO Z5 Pro 5G</td>\n",
       "      <td>4.40</td>\n",
       "      <td>84</td>\n",
       "      <td>Dual Sim, 3G, 4G, 5G, VoLTE,</td>\n",
       "      <td>8</td>\n",
       "      <td>4500</td>\n",
       "      <td>6</td>\n",
       "      <td>64.0</td>\n",
       "      <td>Memory Card (Hybrid)</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>128 GB inbuilt</td>\n",
       "      <td>65W Fast Charging</td>\n",
       "      <td>1080 x 2460 px</td>\n",
       "      <td>Octa Core</td>\n",
       "      <td>Snapdragon 870</td>\n",
       "      <td>iQOO</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1715</th>\n",
       "      <td>itel P55 5G (6GB RAM + 128GB)</td>\n",
       "      <td>4.00</td>\n",
       "      <td>75</td>\n",
       "      <td>Dual Sim, 3G, 4G, 5G, VoLTE,</td>\n",
       "      <td>6</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>128 GB inbuilt</td>\n",
       "      <td>18W Fast Charging</td>\n",
       "      <td>1600 x 720 px</td>\n",
       "      <td>Octa Core</td>\n",
       "      <td>Dimensity 6080</td>\n",
       "      <td>itel</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1716</th>\n",
       "      <td>itel P55 5G (6GB RAM + 128GB)</td>\n",
       "      <td>4.00</td>\n",
       "      <td>75</td>\n",
       "      <td>Dual Sim, 3G, 4G, 5G, VoLTE,</td>\n",
       "      <td>6</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>128 GB inbuilt</td>\n",
       "      <td>18W Fast Charging</td>\n",
       "      <td>1600 x 720 px</td>\n",
       "      <td>Octa Core</td>\n",
       "      <td>Dimensity 6080</td>\n",
       "      <td>itel</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1717</th>\n",
       "      <td>itel P55 5G (6GB RAM + 128GB)</td>\n",
       "      <td>4.00</td>\n",
       "      <td>75</td>\n",
       "      <td>Dual Sim, 3G, 4G, 5G, VoLTE,</td>\n",
       "      <td>6</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>128 GB inbuilt</td>\n",
       "      <td>18W Fast Charging</td>\n",
       "      <td>1600 x 720 px</td>\n",
       "      <td>Octa Core</td>\n",
       "      <td>Dimensity 6080</td>\n",
       "      <td>itel</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1718</th>\n",
       "      <td>itel P55 Plus</td>\n",
       "      <td>4.10</td>\n",
       "      <td>74</td>\n",
       "      <td>Dual Sim, 3G, 4G, VoLTE,</td>\n",
       "      <td>8</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>256 GB inbuilt</td>\n",
       "      <td>45W Fast Charging</td>\n",
       "      <td>720 x 1640 px</td>\n",
       "      <td>Octa Core</td>\n",
       "      <td>Unisoc T606</td>\n",
       "      <td>itel</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1719</th>\n",
       "      <td>itel S24</td>\n",
       "      <td>4.35</td>\n",
       "      <td>75</td>\n",
       "      <td>Dual Sim, 3G, 4G,</td>\n",
       "      <td>8</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>108.0</td>\n",
       "      <td>Memory Card Supported</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>128 GB inbuilt</td>\n",
       "      <td>18W Fast Charging</td>\n",
       "      <td>720 x 1612 px</td>\n",
       "      <td>Octa Core</td>\n",
       "      <td>Helio G91</td>\n",
       "      <td>itel</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1720 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  Name  Rating  Spec_score  \\\n",
       "0                            Vivo Y21T    3.95          74   \n",
       "1                    Motorola Moto G23    4.40          77   \n",
       "2                          Oppo A78 4G    4.25          81   \n",
       "3     POCO M4 Pro 4G (8GB RAM + 128GB)    4.45          81   \n",
       "4                       iQOO Z5 Pro 5G    4.40          84   \n",
       "...                                ...     ...         ...   \n",
       "1715     itel P55 5G (6GB RAM + 128GB)    4.00          75   \n",
       "1716     itel P55 5G (6GB RAM + 128GB)    4.00          75   \n",
       "1717     itel P55 5G (6GB RAM + 128GB)    4.00          75   \n",
       "1718                     itel P55 Plus    4.10          74   \n",
       "1719                          itel S24    4.35          75   \n",
       "\n",
       "                          No_of_sim  Ram  Battery  Display  Camera  \\\n",
       "0         Dual Sim, 3G, 4G, VoLTE,     4     5000        6    50.0   \n",
       "1         Dual Sim, 3G, 4G, VoLTE,     4     5000        6    50.0   \n",
       "2         Dual Sim, 3G, 4G, VoLTE,     8     5000        6    50.0   \n",
       "3         Dual Sim, 3G, 4G, VoLTE,     8     5000        6    64.0   \n",
       "4     Dual Sim, 3G, 4G, 5G, VoLTE,     8     4500        6    64.0   \n",
       "...                             ...  ...      ...      ...     ...   \n",
       "1715  Dual Sim, 3G, 4G, 5G, VoLTE,     6     5000        6    50.0   \n",
       "1716  Dual Sim, 3G, 4G, 5G, VoLTE,     6     5000        6    50.0   \n",
       "1717  Dual Sim, 3G, 4G, 5G, VoLTE,     6     5000        6    50.0   \n",
       "1718      Dual Sim, 3G, 4G, VoLTE,     8     5000        6    50.0   \n",
       "1719             Dual Sim, 3G, 4G,     8     5000        6   108.0   \n",
       "\n",
       "                         External_Memory Android_version  ...  \\\n",
       "0       Memory Card Supported, upto 1 TB              11  ...   \n",
       "1     Memory Card Supported, upto 512 GB              13  ...   \n",
       "2       Memory Card Supported, upto 1 TB              13  ...   \n",
       "3       Memory Card Supported, upto 1 TB              11  ...   \n",
       "4                   Memory Card (Hybrid)              11  ...   \n",
       "...                                  ...             ...  ...   \n",
       "1715    Memory Card Supported, upto 1 TB              13  ...   \n",
       "1716    Memory Card Supported, upto 1 TB              13  ...   \n",
       "1717    Memory Card Supported, upto 1 TB              13  ...   \n",
       "1718    Memory Card Supported, upto 1 TB              13  ...   \n",
       "1719               Memory Card Supported              13  ...   \n",
       "\n",
       "       Inbuilt_memory       fast_charging Screen_resolution   Processor  \\\n",
       "0      128 GB inbuilt   18W Fast Charging     1600 x 720 px   Octa Core   \n",
       "1      128 GB inbuilt   30W Fast Charging     720 x 1600 px   Octa Core   \n",
       "2      128 GB inbuilt   67W Fast Charging    1080 x 2400 px   Octa Core   \n",
       "3      128 GB inbuilt   33W Fast Charging    1080 x 2400 px   Octa Core   \n",
       "4      128 GB inbuilt   65W Fast Charging    1080 x 2460 px   Octa Core   \n",
       "...               ...                 ...               ...         ...   \n",
       "1715   128 GB inbuilt   18W Fast Charging     1600 x 720 px   Octa Core   \n",
       "1716   128 GB inbuilt   18W Fast Charging     1600 x 720 px   Octa Core   \n",
       "1717   128 GB inbuilt   18W Fast Charging     1600 x 720 px   Octa Core   \n",
       "1718   256 GB inbuilt   45W Fast Charging     720 x 1640 px   Octa Core   \n",
       "1719   128 GB inbuilt   18W Fast Charging     720 x 1612 px   Octa Core   \n",
       "\n",
       "       Processor_name   company Spec_score_bin  Battery_bin  Ram_bin  \\\n",
       "0     Snapdragon 680       Vivo              1            0        0   \n",
       "1          Helio  G85  Motorola              1            0        0   \n",
       "2      Snapdragon 680      Oppo              1            0        1   \n",
       "3           Helio G96      POCO              1            0        1   \n",
       "4      Snapdragon 870      iQOO              2            0        1   \n",
       "...               ...       ...            ...          ...      ...   \n",
       "1715   Dimensity 6080      itel              1            0        1   \n",
       "1716   Dimensity 6080      itel              1            0        1   \n",
       "1717   Dimensity 6080      itel              1            0        1   \n",
       "1718      Unisoc T606      itel              1            0        1   \n",
       "1719        Helio G91      itel              1            0        1   \n",
       "\n",
       "      Camera_bin  \n",
       "0              0  \n",
       "1              0  \n",
       "2              0  \n",
       "3              0  \n",
       "4              0  \n",
       "...          ...  \n",
       "1715           0  \n",
       "1716           0  \n",
       "1717           0  \n",
       "1718           0  \n",
       "1719           1  \n",
       "\n",
       "[1720 rows x 21 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numerical_features = [\"Spec_score\", \"Battery\", \"Ram\", \"Camera\"]\n",
    "\n",
    "def discretize_features(df, features, bins=3, labels=False):\n",
    "    for feature in features:\n",
    "        try:\n",
    "            df[f\"{feature}_bin\"] = pd.cut(df[feature], bins=bins, labels=labels) # type: ignore\n",
    "        except Exception as e:\n",
    "            print(f\"Ошибка при дискретизации признака {feature}: {e}\")\n",
    "    return df\n",
    "\n",
    "train_df_disc = discretize_features(train_df_overs, numerical_features)\n",
    "val_df_disc = discretize_features(val_df_overs, numerical_features)\n",
    "test_df_disc = discretize_features(test_df_overs, numerical_features)\n",
    "\n",
    "train_df_disc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Унитарное кодирование категориальных признаков"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Rating</th>\n",
       "      <th>Spec_score</th>\n",
       "      <th>No_of_sim</th>\n",
       "      <th>Ram</th>\n",
       "      <th>Battery</th>\n",
       "      <th>Display</th>\n",
       "      <th>Camera</th>\n",
       "      <th>External_Memory</th>\n",
       "      <th>Android_version</th>\n",
       "      <th>...</th>\n",
       "      <th>Spec_score_bin_2</th>\n",
       "      <th>Battery_bin_0</th>\n",
       "      <th>Battery_bin_1</th>\n",
       "      <th>Battery_bin_2</th>\n",
       "      <th>Ram_bin_0</th>\n",
       "      <th>Ram_bin_1</th>\n",
       "      <th>Ram_bin_2</th>\n",
       "      <th>Camera_bin_0</th>\n",
       "      <th>Camera_bin_1</th>\n",
       "      <th>Camera_bin_2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Vivo Y21T</td>\n",
       "      <td>3.95</td>\n",
       "      <td>74</td>\n",
       "      <td>Dual Sim, 3G, 4G, VoLTE,</td>\n",
       "      <td>4</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Motorola Moto G23</td>\n",
       "      <td>4.40</td>\n",
       "      <td>77</td>\n",
       "      <td>Dual Sim, 3G, 4G, VoLTE,</td>\n",
       "      <td>4</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Memory Card Supported, upto 512 GB</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Oppo A78 4G</td>\n",
       "      <td>4.25</td>\n",
       "      <td>81</td>\n",
       "      <td>Dual Sim, 3G, 4G, VoLTE,</td>\n",
       "      <td>8</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>POCO M4 Pro 4G (8GB RAM + 128GB)</td>\n",
       "      <td>4.45</td>\n",
       "      <td>81</td>\n",
       "      <td>Dual Sim, 3G, 4G, VoLTE,</td>\n",
       "      <td>8</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>64.0</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>iQOO Z5 Pro 5G</td>\n",
       "      <td>4.40</td>\n",
       "      <td>84</td>\n",
       "      <td>Dual Sim, 3G, 4G, 5G, VoLTE,</td>\n",
       "      <td>8</td>\n",
       "      <td>4500</td>\n",
       "      <td>6</td>\n",
       "      <td>64.0</td>\n",
       "      <td>Memory Card (Hybrid)</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1715</th>\n",
       "      <td>itel P55 5G (6GB RAM + 128GB)</td>\n",
       "      <td>4.00</td>\n",
       "      <td>75</td>\n",
       "      <td>Dual Sim, 3G, 4G, 5G, VoLTE,</td>\n",
       "      <td>6</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1716</th>\n",
       "      <td>itel P55 5G (6GB RAM + 128GB)</td>\n",
       "      <td>4.00</td>\n",
       "      <td>75</td>\n",
       "      <td>Dual Sim, 3G, 4G, 5G, VoLTE,</td>\n",
       "      <td>6</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1717</th>\n",
       "      <td>itel P55 5G (6GB RAM + 128GB)</td>\n",
       "      <td>4.00</td>\n",
       "      <td>75</td>\n",
       "      <td>Dual Sim, 3G, 4G, 5G, VoLTE,</td>\n",
       "      <td>6</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1718</th>\n",
       "      <td>itel P55 Plus</td>\n",
       "      <td>4.10</td>\n",
       "      <td>74</td>\n",
       "      <td>Dual Sim, 3G, 4G, VoLTE,</td>\n",
       "      <td>8</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1719</th>\n",
       "      <td>itel S24</td>\n",
       "      <td>4.35</td>\n",
       "      <td>75</td>\n",
       "      <td>Dual Sim, 3G, 4G,</td>\n",
       "      <td>8</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>108.0</td>\n",
       "      <td>Memory Card Supported</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1720 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  Name  Rating  Spec_score  \\\n",
       "0                            Vivo Y21T    3.95          74   \n",
       "1                    Motorola Moto G23    4.40          77   \n",
       "2                          Oppo A78 4G    4.25          81   \n",
       "3     POCO M4 Pro 4G (8GB RAM + 128GB)    4.45          81   \n",
       "4                       iQOO Z5 Pro 5G    4.40          84   \n",
       "...                                ...     ...         ...   \n",
       "1715     itel P55 5G (6GB RAM + 128GB)    4.00          75   \n",
       "1716     itel P55 5G (6GB RAM + 128GB)    4.00          75   \n",
       "1717     itel P55 5G (6GB RAM + 128GB)    4.00          75   \n",
       "1718                     itel P55 Plus    4.10          74   \n",
       "1719                          itel S24    4.35          75   \n",
       "\n",
       "                          No_of_sim  Ram  Battery  Display  Camera  \\\n",
       "0         Dual Sim, 3G, 4G, VoLTE,     4     5000        6    50.0   \n",
       "1         Dual Sim, 3G, 4G, VoLTE,     4     5000        6    50.0   \n",
       "2         Dual Sim, 3G, 4G, VoLTE,     8     5000        6    50.0   \n",
       "3         Dual Sim, 3G, 4G, VoLTE,     8     5000        6    64.0   \n",
       "4     Dual Sim, 3G, 4G, 5G, VoLTE,     8     4500        6    64.0   \n",
       "...                             ...  ...      ...      ...     ...   \n",
       "1715  Dual Sim, 3G, 4G, 5G, VoLTE,     6     5000        6    50.0   \n",
       "1716  Dual Sim, 3G, 4G, 5G, VoLTE,     6     5000        6    50.0   \n",
       "1717  Dual Sim, 3G, 4G, 5G, VoLTE,     6     5000        6    50.0   \n",
       "1718      Dual Sim, 3G, 4G, VoLTE,     8     5000        6    50.0   \n",
       "1719             Dual Sim, 3G, 4G,     8     5000        6   108.0   \n",
       "\n",
       "                         External_Memory Android_version  ...  \\\n",
       "0       Memory Card Supported, upto 1 TB              11  ...   \n",
       "1     Memory Card Supported, upto 512 GB              13  ...   \n",
       "2       Memory Card Supported, upto 1 TB              13  ...   \n",
       "3       Memory Card Supported, upto 1 TB              11  ...   \n",
       "4                   Memory Card (Hybrid)              11  ...   \n",
       "...                                  ...             ...  ...   \n",
       "1715    Memory Card Supported, upto 1 TB              13  ...   \n",
       "1716    Memory Card Supported, upto 1 TB              13  ...   \n",
       "1717    Memory Card Supported, upto 1 TB              13  ...   \n",
       "1718    Memory Card Supported, upto 1 TB              13  ...   \n",
       "1719               Memory Card Supported              13  ...   \n",
       "\n",
       "      Spec_score_bin_2 Battery_bin_0 Battery_bin_1 Battery_bin_2 Ram_bin_0  \\\n",
       "0                False          True         False         False      True   \n",
       "1                False          True         False         False      True   \n",
       "2                False          True         False         False     False   \n",
       "3                False          True         False         False     False   \n",
       "4                 True          True         False         False     False   \n",
       "...                ...           ...           ...           ...       ...   \n",
       "1715             False          True         False         False     False   \n",
       "1716             False          True         False         False     False   \n",
       "1717             False          True         False         False     False   \n",
       "1718             False          True         False         False     False   \n",
       "1719             False          True         False         False     False   \n",
       "\n",
       "     Ram_bin_1 Ram_bin_2  Camera_bin_0  Camera_bin_1  Camera_bin_2  \n",
       "0        False     False          True         False         False  \n",
       "1        False     False          True         False         False  \n",
       "2         True     False          True         False         False  \n",
       "3         True     False          True         False         False  \n",
       "4         True     False          True         False         False  \n",
       "...        ...       ...           ...           ...           ...  \n",
       "1715      True     False          True         False         False  \n",
       "1716      True     False          True         False         False  \n",
       "1717      True     False          True         False         False  \n",
       "1718      True     False          True         False         False  \n",
       "1719      True     False         False          True         False  \n",
       "\n",
       "[1720 rows x 29 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "categorical_features = [\"Spec_score_bin\", \"Battery_bin\", \"Ram_bin\", \"Camera_bin\"]\n",
    "\n",
    "train_df_enc = pd.get_dummies(train_df_disc, columns=categorical_features)\n",
    "val_df_enc = pd.get_dummies(val_df_disc, columns=categorical_features)\n",
    "test_df_enc = pd.get_dummies(test_df_disc, columns=categorical_features)\n",
    "\n",
    "train_df_enc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Ручной синтез признаков."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Rating</th>\n",
       "      <th>Spec_score</th>\n",
       "      <th>No_of_sim</th>\n",
       "      <th>Ram</th>\n",
       "      <th>Battery</th>\n",
       "      <th>Display</th>\n",
       "      <th>Camera</th>\n",
       "      <th>External_Memory</th>\n",
       "      <th>Android_version</th>\n",
       "      <th>...</th>\n",
       "      <th>Battery_bin_0</th>\n",
       "      <th>Battery_bin_1</th>\n",
       "      <th>Battery_bin_2</th>\n",
       "      <th>Ram_bin_0</th>\n",
       "      <th>Ram_bin_1</th>\n",
       "      <th>Ram_bin_2</th>\n",
       "      <th>Camera_bin_0</th>\n",
       "      <th>Camera_bin_1</th>\n",
       "      <th>Camera_bin_2</th>\n",
       "      <th>Camera_to_Display_Ratio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Vivo Y21T</td>\n",
       "      <td>3.95</td>\n",
       "      <td>74</td>\n",
       "      <td>Dual Sim, 3G, 4G, VoLTE,</td>\n",
       "      <td>4</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>8.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Motorola Moto G23</td>\n",
       "      <td>4.40</td>\n",
       "      <td>77</td>\n",
       "      <td>Dual Sim, 3G, 4G, VoLTE,</td>\n",
       "      <td>4</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Memory Card Supported, upto 512 GB</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>8.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Oppo A78 4G</td>\n",
       "      <td>4.25</td>\n",
       "      <td>81</td>\n",
       "      <td>Dual Sim, 3G, 4G, VoLTE,</td>\n",
       "      <td>8</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>8.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>POCO M4 Pro 4G (8GB RAM + 128GB)</td>\n",
       "      <td>4.45</td>\n",
       "      <td>81</td>\n",
       "      <td>Dual Sim, 3G, 4G, VoLTE,</td>\n",
       "      <td>8</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>64.0</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>10.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>iQOO Z5 Pro 5G</td>\n",
       "      <td>4.40</td>\n",
       "      <td>84</td>\n",
       "      <td>Dual Sim, 3G, 4G, 5G, VoLTE,</td>\n",
       "      <td>8</td>\n",
       "      <td>4500</td>\n",
       "      <td>6</td>\n",
       "      <td>64.0</td>\n",
       "      <td>Memory Card (Hybrid)</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>10.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1715</th>\n",
       "      <td>itel P55 5G (6GB RAM + 128GB)</td>\n",
       "      <td>4.00</td>\n",
       "      <td>75</td>\n",
       "      <td>Dual Sim, 3G, 4G, 5G, VoLTE,</td>\n",
       "      <td>6</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>8.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1716</th>\n",
       "      <td>itel P55 5G (6GB RAM + 128GB)</td>\n",
       "      <td>4.00</td>\n",
       "      <td>75</td>\n",
       "      <td>Dual Sim, 3G, 4G, 5G, VoLTE,</td>\n",
       "      <td>6</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>8.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1717</th>\n",
       "      <td>itel P55 5G (6GB RAM + 128GB)</td>\n",
       "      <td>4.00</td>\n",
       "      <td>75</td>\n",
       "      <td>Dual Sim, 3G, 4G, 5G, VoLTE,</td>\n",
       "      <td>6</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>8.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1718</th>\n",
       "      <td>itel P55 Plus</td>\n",
       "      <td>4.10</td>\n",
       "      <td>74</td>\n",
       "      <td>Dual Sim, 3G, 4G, VoLTE,</td>\n",
       "      <td>8</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>8.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1719</th>\n",
       "      <td>itel S24</td>\n",
       "      <td>4.35</td>\n",
       "      <td>75</td>\n",
       "      <td>Dual Sim, 3G, 4G,</td>\n",
       "      <td>8</td>\n",
       "      <td>5000</td>\n",
       "      <td>6</td>\n",
       "      <td>108.0</td>\n",
       "      <td>Memory Card Supported</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>18.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1720 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  Name  Rating  Spec_score  \\\n",
       "0                            Vivo Y21T    3.95          74   \n",
       "1                    Motorola Moto G23    4.40          77   \n",
       "2                          Oppo A78 4G    4.25          81   \n",
       "3     POCO M4 Pro 4G (8GB RAM + 128GB)    4.45          81   \n",
       "4                       iQOO Z5 Pro 5G    4.40          84   \n",
       "...                                ...     ...         ...   \n",
       "1715     itel P55 5G (6GB RAM + 128GB)    4.00          75   \n",
       "1716     itel P55 5G (6GB RAM + 128GB)    4.00          75   \n",
       "1717     itel P55 5G (6GB RAM + 128GB)    4.00          75   \n",
       "1718                     itel P55 Plus    4.10          74   \n",
       "1719                          itel S24    4.35          75   \n",
       "\n",
       "                          No_of_sim  Ram  Battery  Display  Camera  \\\n",
       "0         Dual Sim, 3G, 4G, VoLTE,     4     5000        6    50.0   \n",
       "1         Dual Sim, 3G, 4G, VoLTE,     4     5000        6    50.0   \n",
       "2         Dual Sim, 3G, 4G, VoLTE,     8     5000        6    50.0   \n",
       "3         Dual Sim, 3G, 4G, VoLTE,     8     5000        6    64.0   \n",
       "4     Dual Sim, 3G, 4G, 5G, VoLTE,     8     4500        6    64.0   \n",
       "...                             ...  ...      ...      ...     ...   \n",
       "1715  Dual Sim, 3G, 4G, 5G, VoLTE,     6     5000        6    50.0   \n",
       "1716  Dual Sim, 3G, 4G, 5G, VoLTE,     6     5000        6    50.0   \n",
       "1717  Dual Sim, 3G, 4G, 5G, VoLTE,     6     5000        6    50.0   \n",
       "1718      Dual Sim, 3G, 4G, VoLTE,     8     5000        6    50.0   \n",
       "1719             Dual Sim, 3G, 4G,     8     5000        6   108.0   \n",
       "\n",
       "                         External_Memory Android_version  ...  Battery_bin_0  \\\n",
       "0       Memory Card Supported, upto 1 TB              11  ...           True   \n",
       "1     Memory Card Supported, upto 512 GB              13  ...           True   \n",
       "2       Memory Card Supported, upto 1 TB              13  ...           True   \n",
       "3       Memory Card Supported, upto 1 TB              11  ...           True   \n",
       "4                   Memory Card (Hybrid)              11  ...           True   \n",
       "...                                  ...             ...  ...            ...   \n",
       "1715    Memory Card Supported, upto 1 TB              13  ...           True   \n",
       "1716    Memory Card Supported, upto 1 TB              13  ...           True   \n",
       "1717    Memory Card Supported, upto 1 TB              13  ...           True   \n",
       "1718    Memory Card Supported, upto 1 TB              13  ...           True   \n",
       "1719               Memory Card Supported              13  ...           True   \n",
       "\n",
       "     Battery_bin_1 Battery_bin_2 Ram_bin_0 Ram_bin_1 Ram_bin_2 Camera_bin_0  \\\n",
       "0            False         False      True     False     False         True   \n",
       "1            False         False      True     False     False         True   \n",
       "2            False         False     False      True     False         True   \n",
       "3            False         False     False      True     False         True   \n",
       "4            False         False     False      True     False         True   \n",
       "...            ...           ...       ...       ...       ...          ...   \n",
       "1715         False         False     False      True     False         True   \n",
       "1716         False         False     False      True     False         True   \n",
       "1717         False         False     False      True     False         True   \n",
       "1718         False         False     False      True     False         True   \n",
       "1719         False         False     False      True     False        False   \n",
       "\n",
       "      Camera_bin_1  Camera_bin_2  Camera_to_Display_Ratio  \n",
       "0            False         False                 8.333333  \n",
       "1            False         False                 8.333333  \n",
       "2            False         False                 8.333333  \n",
       "3            False         False                10.666667  \n",
       "4            False         False                10.666667  \n",
       "...            ...           ...                      ...  \n",
       "1715         False         False                 8.333333  \n",
       "1716         False         False                 8.333333  \n",
       "1717         False         False                 8.333333  \n",
       "1718         False         False                 8.333333  \n",
       "1719          True         False                18.000000  \n",
       "\n",
       "[1720 rows x 30 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df_enc[\"Camera_to_Display_Ratio\"] = (train_df_enc[\"Camera\"] / train_df_enc[\"Display\"])\n",
    "val_df_enc[\"Camera_to_Display_Ratio\"] = val_df_enc[\"Camera\"] / val_df_enc[\"Display\"]\n",
    "test_df_enc[\"Camera_to_Display_Ratio\"] = test_df_enc[\"Camera\"] / test_df_enc[\"Display\"]\n",
    "\n",
    "train_df_enc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Масштабирование признаков"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Rating</th>\n",
       "      <th>Spec_score</th>\n",
       "      <th>No_of_sim</th>\n",
       "      <th>Ram</th>\n",
       "      <th>Battery</th>\n",
       "      <th>Display</th>\n",
       "      <th>Camera</th>\n",
       "      <th>External_Memory</th>\n",
       "      <th>Android_version</th>\n",
       "      <th>...</th>\n",
       "      <th>Battery_bin_0</th>\n",
       "      <th>Battery_bin_1</th>\n",
       "      <th>Battery_bin_2</th>\n",
       "      <th>Ram_bin_0</th>\n",
       "      <th>Ram_bin_1</th>\n",
       "      <th>Ram_bin_2</th>\n",
       "      <th>Camera_bin_0</th>\n",
       "      <th>Camera_bin_1</th>\n",
       "      <th>Camera_bin_2</th>\n",
       "      <th>Camera_to_Display_Ratio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Vivo Y21T</td>\n",
       "      <td>3.95</td>\n",
       "      <td>74</td>\n",
       "      <td>Dual Sim, 3G, 4G, VoLTE,</td>\n",
       "      <td>-1.388963</td>\n",
       "      <td>0.206174</td>\n",
       "      <td>0.096622</td>\n",
       "      <td>-0.240789</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>8.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Motorola Moto G23</td>\n",
       "      <td>4.40</td>\n",
       "      <td>77</td>\n",
       "      <td>Dual Sim, 3G, 4G, VoLTE,</td>\n",
       "      <td>-1.388963</td>\n",
       "      <td>0.206174</td>\n",
       "      <td>0.096622</td>\n",
       "      <td>-0.240789</td>\n",
       "      <td>Memory Card Supported, upto 512 GB</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>8.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Oppo A78 4G</td>\n",
       "      <td>4.25</td>\n",
       "      <td>81</td>\n",
       "      <td>Dual Sim, 3G, 4G, VoLTE,</td>\n",
       "      <td>0.720078</td>\n",
       "      <td>0.206174</td>\n",
       "      <td>0.096622</td>\n",
       "      <td>-0.240789</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>8.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>POCO M4 Pro 4G (8GB RAM + 128GB)</td>\n",
       "      <td>4.45</td>\n",
       "      <td>81</td>\n",
       "      <td>Dual Sim, 3G, 4G, VoLTE,</td>\n",
       "      <td>0.720078</td>\n",
       "      <td>0.206174</td>\n",
       "      <td>0.096622</td>\n",
       "      <td>0.275662</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>10.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>iQOO Z5 Pro 5G</td>\n",
       "      <td>4.40</td>\n",
       "      <td>84</td>\n",
       "      <td>Dual Sim, 3G, 4G, 5G, VoLTE,</td>\n",
       "      <td>0.720078</td>\n",
       "      <td>-0.675789</td>\n",
       "      <td>0.096622</td>\n",
       "      <td>0.275662</td>\n",
       "      <td>Memory Card (Hybrid)</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>10.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1715</th>\n",
       "      <td>itel P55 5G (6GB RAM + 128GB)</td>\n",
       "      <td>4.00</td>\n",
       "      <td>75</td>\n",
       "      <td>Dual Sim, 3G, 4G, 5G, VoLTE,</td>\n",
       "      <td>-0.334442</td>\n",
       "      <td>0.206174</td>\n",
       "      <td>0.096622</td>\n",
       "      <td>-0.240789</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>8.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1716</th>\n",
       "      <td>itel P55 5G (6GB RAM + 128GB)</td>\n",
       "      <td>4.00</td>\n",
       "      <td>75</td>\n",
       "      <td>Dual Sim, 3G, 4G, 5G, VoLTE,</td>\n",
       "      <td>-0.334442</td>\n",
       "      <td>0.206174</td>\n",
       "      <td>0.096622</td>\n",
       "      <td>-0.240789</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>8.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1717</th>\n",
       "      <td>itel P55 5G (6GB RAM + 128GB)</td>\n",
       "      <td>4.00</td>\n",
       "      <td>75</td>\n",
       "      <td>Dual Sim, 3G, 4G, 5G, VoLTE,</td>\n",
       "      <td>-0.334442</td>\n",
       "      <td>0.206174</td>\n",
       "      <td>0.096622</td>\n",
       "      <td>-0.240789</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>8.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1718</th>\n",
       "      <td>itel P55 Plus</td>\n",
       "      <td>4.10</td>\n",
       "      <td>74</td>\n",
       "      <td>Dual Sim, 3G, 4G, VoLTE,</td>\n",
       "      <td>0.720078</td>\n",
       "      <td>0.206174</td>\n",
       "      <td>0.096622</td>\n",
       "      <td>-0.240789</td>\n",
       "      <td>Memory Card Supported, upto 1 TB</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>8.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1719</th>\n",
       "      <td>itel S24</td>\n",
       "      <td>4.35</td>\n",
       "      <td>75</td>\n",
       "      <td>Dual Sim, 3G, 4G,</td>\n",
       "      <td>0.720078</td>\n",
       "      <td>0.206174</td>\n",
       "      <td>0.096622</td>\n",
       "      <td>1.898794</td>\n",
       "      <td>Memory Card Supported</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>18.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1720 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  Name  Rating  Spec_score  \\\n",
       "0                            Vivo Y21T    3.95          74   \n",
       "1                    Motorola Moto G23    4.40          77   \n",
       "2                          Oppo A78 4G    4.25          81   \n",
       "3     POCO M4 Pro 4G (8GB RAM + 128GB)    4.45          81   \n",
       "4                       iQOO Z5 Pro 5G    4.40          84   \n",
       "...                                ...     ...         ...   \n",
       "1715     itel P55 5G (6GB RAM + 128GB)    4.00          75   \n",
       "1716     itel P55 5G (6GB RAM + 128GB)    4.00          75   \n",
       "1717     itel P55 5G (6GB RAM + 128GB)    4.00          75   \n",
       "1718                     itel P55 Plus    4.10          74   \n",
       "1719                          itel S24    4.35          75   \n",
       "\n",
       "                          No_of_sim       Ram   Battery   Display    Camera  \\\n",
       "0         Dual Sim, 3G, 4G, VoLTE,  -1.388963  0.206174  0.096622 -0.240789   \n",
       "1         Dual Sim, 3G, 4G, VoLTE,  -1.388963  0.206174  0.096622 -0.240789   \n",
       "2         Dual Sim, 3G, 4G, VoLTE,   0.720078  0.206174  0.096622 -0.240789   \n",
       "3         Dual Sim, 3G, 4G, VoLTE,   0.720078  0.206174  0.096622  0.275662   \n",
       "4     Dual Sim, 3G, 4G, 5G, VoLTE,   0.720078 -0.675789  0.096622  0.275662   \n",
       "...                             ...       ...       ...       ...       ...   \n",
       "1715  Dual Sim, 3G, 4G, 5G, VoLTE,  -0.334442  0.206174  0.096622 -0.240789   \n",
       "1716  Dual Sim, 3G, 4G, 5G, VoLTE,  -0.334442  0.206174  0.096622 -0.240789   \n",
       "1717  Dual Sim, 3G, 4G, 5G, VoLTE,  -0.334442  0.206174  0.096622 -0.240789   \n",
       "1718      Dual Sim, 3G, 4G, VoLTE,   0.720078  0.206174  0.096622 -0.240789   \n",
       "1719             Dual Sim, 3G, 4G,   0.720078  0.206174  0.096622  1.898794   \n",
       "\n",
       "                         External_Memory Android_version  ...  Battery_bin_0  \\\n",
       "0       Memory Card Supported, upto 1 TB              11  ...           True   \n",
       "1     Memory Card Supported, upto 512 GB              13  ...           True   \n",
       "2       Memory Card Supported, upto 1 TB              13  ...           True   \n",
       "3       Memory Card Supported, upto 1 TB              11  ...           True   \n",
       "4                   Memory Card (Hybrid)              11  ...           True   \n",
       "...                                  ...             ...  ...            ...   \n",
       "1715    Memory Card Supported, upto 1 TB              13  ...           True   \n",
       "1716    Memory Card Supported, upto 1 TB              13  ...           True   \n",
       "1717    Memory Card Supported, upto 1 TB              13  ...           True   \n",
       "1718    Memory Card Supported, upto 1 TB              13  ...           True   \n",
       "1719               Memory Card Supported              13  ...           True   \n",
       "\n",
       "     Battery_bin_1 Battery_bin_2 Ram_bin_0 Ram_bin_1 Ram_bin_2 Camera_bin_0  \\\n",
       "0            False         False      True     False     False         True   \n",
       "1            False         False      True     False     False         True   \n",
       "2            False         False     False      True     False         True   \n",
       "3            False         False     False      True     False         True   \n",
       "4            False         False     False      True     False         True   \n",
       "...            ...           ...       ...       ...       ...          ...   \n",
       "1715         False         False     False      True     False         True   \n",
       "1716         False         False     False      True     False         True   \n",
       "1717         False         False     False      True     False         True   \n",
       "1718         False         False     False      True     False         True   \n",
       "1719         False         False     False      True     False        False   \n",
       "\n",
       "      Camera_bin_1  Camera_bin_2  Camera_to_Display_Ratio  \n",
       "0            False         False                 8.333333  \n",
       "1            False         False                 8.333333  \n",
       "2            False         False                 8.333333  \n",
       "3            False         False                10.666667  \n",
       "4            False         False                10.666667  \n",
       "...            ...           ...                      ...  \n",
       "1715         False         False                 8.333333  \n",
       "1716         False         False                 8.333333  \n",
       "1717         False         False                 8.333333  \n",
       "1718         False         False                 8.333333  \n",
       "1719          True         False                18.000000  \n",
       "\n",
       "[1720 rows x 30 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scaler = StandardScaler()\n",
    "\n",
    "numerical_features = [\n",
    "    \"Ram\",\n",
    "    \"Battery\",\n",
    "    \"Display\",\n",
    "    \"Camera\",\n",
    "]\n",
    "\n",
    "train_df_enc[numerical_features] = scaler.fit_transform(\n",
    "    train_df_enc[numerical_features]\n",
    ")\n",
    "val_df_enc[numerical_features] = scaler.transform(val_df_enc[numerical_features])\n",
    "test_df_enc[numerical_features] = scaler.transform(test_df_enc[numerical_features])\n",
    "\n",
    "train_df_enc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Конструирование признаков с помощью Featuretools"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\user\\source\\repos\\mai_pi-33_zakharov\\.venv\\Lib\\site-packages\\featuretools\\entityset\\entityset.py:1733: UserWarning: index id not found in dataframe, creating new integer column\n",
      "  warnings.warn(\n",
      "c:\\Users\\user\\source\\repos\\mai_pi-33_zakharov\\.venv\\Lib\\site-packages\\woodwork\\type_sys\\utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
      "  pd.to_datetime(\n",
      "c:\\Users\\user\\source\\repos\\mai_pi-33_zakharov\\.venv\\Lib\\site-packages\\woodwork\\type_sys\\utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
      "  pd.to_datetime(\n",
      "c:\\Users\\user\\source\\repos\\mai_pi-33_zakharov\\.venv\\Lib\\site-packages\\woodwork\\type_sys\\utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
      "  pd.to_datetime(\n",
      "c:\\Users\\user\\source\\repos\\mai_pi-33_zakharov\\.venv\\Lib\\site-packages\\woodwork\\type_sys\\utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
      "  pd.to_datetime(\n",
      "c:\\Users\\user\\source\\repos\\mai_pi-33_zakharov\\.venv\\Lib\\site-packages\\woodwork\\type_sys\\utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
      "  pd.to_datetime(\n",
      "c:\\Users\\user\\source\\repos\\mai_pi-33_zakharov\\.venv\\Lib\\site-packages\\woodwork\\type_sys\\utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
      "  pd.to_datetime(\n",
      "c:\\Users\\user\\source\\repos\\mai_pi-33_zakharov\\.venv\\Lib\\site-packages\\woodwork\\type_sys\\utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
      "  pd.to_datetime(\n",
      "c:\\Users\\user\\source\\repos\\mai_pi-33_zakharov\\.venv\\Lib\\site-packages\\woodwork\\type_sys\\utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
      "  pd.to_datetime(\n",
      "c:\\Users\\user\\source\\repos\\mai_pi-33_zakharov\\.venv\\Lib\\site-packages\\woodwork\\type_sys\\utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
      "  pd.to_datetime(\n",
      "c:\\Users\\user\\source\\repos\\mai_pi-33_zakharov\\.venv\\Lib\\site-packages\\woodwork\\type_sys\\utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
      "  pd.to_datetime(\n",
      "c:\\Users\\user\\source\\repos\\mai_pi-33_zakharov\\.venv\\Lib\\site-packages\\woodwork\\type_sys\\utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
      "  pd.to_datetime(\n",
      "c:\\Users\\user\\source\\repos\\mai_pi-33_zakharov\\.venv\\Lib\\site-packages\\woodwork\\type_sys\\utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
      "  pd.to_datetime(\n",
      "c:\\Users\\user\\source\\repos\\mai_pi-33_zakharov\\.venv\\Lib\\site-packages\\woodwork\\type_sys\\utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
      "  pd.to_datetime(\n",
      "c:\\Users\\user\\source\\repos\\mai_pi-33_zakharov\\.venv\\Lib\\site-packages\\woodwork\\type_sys\\utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
      "  pd.to_datetime(\n",
      "c:\\Users\\user\\source\\repos\\mai_pi-33_zakharov\\.venv\\Lib\\site-packages\\woodwork\\type_sys\\utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
      "  pd.to_datetime(\n",
      "c:\\Users\\user\\source\\repos\\mai_pi-33_zakharov\\.venv\\Lib\\site-packages\\woodwork\\type_sys\\utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
      "  pd.to_datetime(\n",
      "c:\\Users\\user\\source\\repos\\mai_pi-33_zakharov\\.venv\\Lib\\site-packages\\woodwork\\type_sys\\utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
      "  pd.to_datetime(\n",
      "c:\\Users\\user\\source\\repos\\mai_pi-33_zakharov\\.venv\\Lib\\site-packages\\woodwork\\type_sys\\utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
      "  pd.to_datetime(\n",
      "c:\\Users\\user\\source\\repos\\mai_pi-33_zakharov\\.venv\\Lib\\site-packages\\woodwork\\type_sys\\utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
      "  pd.to_datetime(\n",
      "c:\\Users\\user\\source\\repos\\mai_pi-33_zakharov\\.venv\\Lib\\site-packages\\woodwork\\type_sys\\utils.py:33: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
      "  pd.to_datetime(\n",
      "c:\\Users\\user\\source\\repos\\mai_pi-33_zakharov\\.venv\\Lib\\site-packages\\featuretools\\synthesis\\deep_feature_synthesis.py:169: UserWarning: Only one dataframe in entityset, changing max_depth to 1 since deeper features cannot be created\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[<Feature: Rating>,\n",
       " <Feature: Spec_score>,\n",
       " <Feature: No_of_sim>,\n",
       " <Feature: Ram>,\n",
       " <Feature: Battery>,\n",
       " <Feature: Display>,\n",
       " <Feature: Camera>,\n",
       " <Feature: External_Memory>,\n",
       " <Feature: Android_version>,\n",
       " <Feature: Price>,\n",
       " <Feature: Inbuilt_memory>,\n",
       " <Feature: fast_charging>,\n",
       " <Feature: Screen_resolution>,\n",
       " <Feature: Processor>,\n",
       " <Feature: Processor_name>,\n",
       " <Feature: company>,\n",
       " <Feature: Spec_score_bin_0>,\n",
       " <Feature: Spec_score_bin_1>,\n",
       " <Feature: Spec_score_bin_2>,\n",
       " <Feature: Battery_bin_0>,\n",
       " <Feature: Battery_bin_1>,\n",
       " <Feature: Battery_bin_2>,\n",
       " <Feature: Ram_bin_0>,\n",
       " <Feature: Ram_bin_1>,\n",
       " <Feature: Ram_bin_2>,\n",
       " <Feature: Camera_bin_0>,\n",
       " <Feature: Camera_bin_1>,\n",
       " <Feature: Camera_bin_2>,\n",
       " <Feature: Camera_to_Display_Ratio>]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "es = ft.EntitySet(id=\"mobile_data\")\n",
    "es = es.add_dataframe(dataframe_name=\"train\", dataframe=train_df_enc, index=\"id\")\n",
    "feature_matrix, feature_defs = ft.dfs(\n",
    "    entityset=es, target_dataframe_name=\"train\", max_depth=2\n",
    ")\n",
    "\n",
    "feature_defs"
   ]
  }
 ],
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